Publications

2020

  • F. Han, R. Guerrero, and V. Pavlovic, “CookGAN: Meal Image Synthesis from Ingredients,” in Winter Conference on Applications of Computer Vision (WACV ’20), Aspen, Colorado, 2020.
    [BibTeX]
    @InProceedings{han20wacv,
    author = {Fangda Han and Ricardo Guerrero and Vladimir Pavlovic},
    booktitle = {Winter Conference on Applications of Computer Vision ({WACV} ’20)},
    title = {{CookGAN}: Meal Image Synthesis from Ingredients},
    year = {2020},
    address = {Aspen, Colorado},
    month = mar,
    date-added = {2019-09-09 15:01:10 -0400},
    date-modified = {2019-09-09 15:02:39 -0400},
    }

2019

  • S. S. Sohn, S. Moon, H. Zhou, S. Yoon, V. Pavlovic, and M. Kapadia, “Deep Crowd-Flow Prediction in Built Environments,” in Neural Information Processing Systems NeurIPS, Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response, Montreal, Canada, 2019.
    [BibTeX]
    @InProceedings{son19nipsws,
    author = {Samuel S. Sohn and Seonghyeon Moon and Honglu Zhou and Sejong Yoon and Vladimir Pavlovic and Mubbasir Kapadia},
    booktitle = {Neural Information Processing Systems {NeurIPS}, Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response},
    title = {Deep Crowd-Flow Prediction in Built Environments},
    year = {2019},
    address = {Montreal, Canada},
    month = dec,
    date-added = {2019-09-09 15:01:10 -0400},
    date-modified = {2019-09-09 15:02:39 -0400},
    }

  • M. Lee, O. Rudovic, V. Pavlovic, and M. Pantic, “Fast Adaptation of Personalized Deep Learning for Facial Action Unit Detection,” in Int’l Joint Conference on Artificial Intelligence IJCNN, Workshop on Affective Computing, Macao, China, 2019.
    [BibTeX]
    @InProceedings{lee19ijcaiws,
    author = {Mihee Lee and Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    booktitle = {Int'l Joint Conference on Artificial Intelligence {IJCNN}, Workshop on Affective Computing},
    title = {Fast Adaptation of Personalized Deep Learning for Facial Action Unit Detection},
    year = {2019},
    address = {Macao, China},
    month = aug,
    date-added = {2019-09-09 15:01:10 -0400},
    date-modified = {2019-09-09 15:02:39 -0400},
    }

  • M. Kim, Y. Wang, P. Sahu, and V. Pavlovic, “Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement,” in IEEE International Conference on Computer Vision, ICCV, Seoul, Korea, 2019.
    [BibTeX]
    @InProceedings{kim19iccv,
    author = {Minyoung Kim and Yuting Wang and Pritish Sahu and Vladimir Pavlovic},
    booktitle = {{IEEE} International Conference on Computer Vision, {ICCV}},
    title = {Bayes-Factor-{VAE}: Hierarchical {Bayesian} Deep Auto-Encoder Models for Factor Disentanglement},
    year = {2019},
    address = {Seoul, Korea},
    month = oct,
    date-added = {2019-09-05 20:58:51 +0100},
    date-modified = {2019-09-05 21:00:05 +0100},
    }

  • B. Gholami, P. Sahu, M. Kim, and V. Pavlovic, “Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation,” in IEEE International Conference on Computer Vision, ICCV, 6th Workshop on Transferring and Adapting Source Knowledge in Computer Vision, Seoul, Korea, 2019.
    [BibTeX]
    @InProceedings{gholami19iccvws,
    author = {Behnam Gholami and Pritish Sahu and Minyoung Kim and Vladimir Pavlovic},
    booktitle = {{IEEE} International Conference on Computer Vision, {ICCV}, 6th Workshop on Transferring and Adapting Source Knowledge in Computer Vision},
    title = {Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation},
    year = {2019},
    address = {Seoul, Korea},
    month = oct,
    date-added = {2019-09-05 20:54:25 +0100},
    date-modified = {2019-09-05 20:57:09 +0100},
    }

  • J. Li, R. Guerrero, and V. Pavlovic, “Deep Cooking: Predicting Relative Food Ingredient Amounts from Images,” in 5th International Workshop on Multimedia Assisted Dietary Management (MADiMa ’19), Nice, France, 2019. doi:10.1145/3347448.3357164
    [BibTeX]
    @InProceedings{li19madima,
    author = {Jiatong Li and Ricardo Guerrero and Vladimir Pavlovic},
    booktitle = {5th International Workshop on Multimedia Assisted Dietary Management ({MADiMa} '19)},
    title = {Deep Cooking: Predicting Relative Food Ingredient Amounts from Images},
    year = {2019},
    address = {Nice, France},
    month = oct,
    date-added = {2019-09-05 20:51:44 +0100},
    date-modified = {2019-09-05 20:52:48 +0100},
    doi = {10.1145/3347448.3357164},
    }

  • J. Li, R. Guerrero, and V. Pavlovic, “Deep Cooking: Predicting Food Ingredient Amounts from Images,” in Int’l Joint Conference on Artificial Intelligence IJCNN, Workshop on AI and Food, Macao, China, 2019.
    [BibTeX]
    @InProceedings{li19ijcai,
    author = {Jiatong Li and Ricardo Guerrero and Vladimir Pavlovic},
    booktitle = {Int'l Joint Conference on Artificial Intelligence {IJCNN}, Workshop on AI and Food},
    title = {Deep Cooking: Predicting Food Ingredient Amounts from Images},
    year = {2019},
    address = {Macao, China},
    month = aug,
    date-added = {2019-09-05 20:49:20 +0100},
    date-modified = {2019-09-05 20:50:24 +0100},
    }

  • G. Qiao, H. Zhou, S. Yoon, M. Kapadia, and V. Pavlovic, “Scenario Generalization of Data-driven Imitation Models in Crowd Simulation,” in ACM SIGGRAPH Conference on Motion, Interaction and Games (MIG), 2019. doi:10.1145/3359566.3360087
    [BibTeX]
    @InProceedings{gang19mig,
    author = {Gang Qiao and Honglu Zhou and Sejong Yoon and Mubbasir Kapadia and Vladimir Pavlovic},
    booktitle = {ACM SIGGRAPH Conference on Motion, Interaction and Games (MIG)},
    title = {Scenario Generalization of Data-driven Imitation Models in Crowd Simulation},
    year = {2019},
    date-added = {2019-09-05 20:43:26 +0100},
    date-modified = {2019-09-05 20:46:44 +0100},
    doi = {10.1145/3359566.3360087},
    }

  • L. Zhao, F. Han, X. Peng, X. Zhang, M. Kapadia, V. Pavlovic, and D. N. Metaxas, “Cartoonish sketch-based face editing in videos using identity deformation transfer,” Computers & Graphics, vol. 79, p. 58–68, 2019. doi:10.1016/j.cag.2019.01.004
    [BibTeX]
    @Article{ZhaoH0ZKPM19,
    author = {Long Zhao and Fangda Han and Xi Peng and Xun Zhang and Mubbasir Kapadia and Vladimir Pavlovic and Dimitris N. Metaxas},
    journal = {Computers {\&} Graphics},
    title = {Cartoonish sketch-based face editing in videos using identity deformation transfer},
    year = {2019},
    pages = {58--68},
    volume = {79},
    doi = {10.1016/j.cag.2019.01.004},
    }

  • L. Sheng, J. Cai, T. -, V. Pavlovic, and K. N. Ngan, “Visibility Constrained Generative Model for Depth-Based 3D Facial Pose Tracking,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 41, iss. 8, p. 1994–2007, 2019. doi:10.1109/tpami.2018.2877675
    [BibTeX]
    @Article{ShengCCPN19,
    author = {Lu Sheng and Jianfei Cai and Tat{-}Jen Cham and Vladimir Pavlovic and King Ngi Ngan},
    journal = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
    title = {Visibility Constrained Generative Model for Depth-Based 3D Facial Pose Tracking},
    year = {2019},
    number = {8},
    pages = {1994--2007},
    volume = {41},
    doi = {10.1109/tpami.2018.2877675},
    }

  • M. Kim, Y. Wang, P. Sahu, and V. Pavlovic, “Relevance Factor VAE: Learning and Identifying Disentangled Factors,” CoRR, vol. abs/1902.01568, 2019.
    [BibTeX]
    @article{kim19rfvae_arxiv,
    Author = {Minyoung Kim and Yuting Wang and Pritish Sahu and Vladimir Pavlovic},
    Journal = {CoRR},
    Title = {Relevance Factor {VAE:} Learning and Identifying Disentangled Factors},
    Volume = {abs/1902.01568},
    Year = {2019}}

  • M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised visual domain adaptation: A deep max-margin Gaussian process approach,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, p. 4380–4390.
    [BibTeX]
    @inproceedings{kim2019ugpda,
    Author = {Kim, Minyoung and Sahu, Pritish and Gholami, Behnam and Pavlovic, Vladimir},
    Booktitle = {Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition},
    Pages = {4380--4390},
    Title = {Unsupervised visual domain adaptation: A deep max-margin {Gaussian} process approach},
    Year = {2019}}

  • M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach,” CoRR, vol. abs/1902.08727, 2019.
    [BibTeX]
    @article{kim19ugpda_arxiv,
    Author = {Minyoung Kim and Pritish Sahu and Behnam Gholami and Vladimir Pavlovic},
    Journal = {CoRR},
    Title = {Unsupervised Visual Domain Adaptation: {A} Deep Max-Margin {Gaussian} Process Approach},
    Volume = {abs/1902.08727},
    Year = {2019}}

  • L. Sheng, J. Cai, T. -, V. Pavlovic, and K. N. Ngan, “Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking,” CoRR, vol. abs/1905.02114, 2019. doi:10.1109/tpami.2018.2877675
    [BibTeX]
    @Article{sheng19vcgm_arxiv,
    author = {Lu Sheng and Jianfei Cai and Tat{-}Jen Cham and Vladimir Pavlovic and King Ngi Ngan},
    journal = {CoRR},
    title = {Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking},
    year = {2019},
    volume = {abs/1905.02114},
    doi = {10.1109/tpami.2018.2877675},
    }

  • I. H. Laradji, M. Schmidt, V. Pavlovic, and M. Kim, “Efficient Deep Gaussian Process Models for Variable-Sized Input,” in Int’l Joint Conference on Neural Networks IJCNN, Budapest, Hungary, 2019. doi:10.1109/ijcnn.2019.8851768
    [BibTeX]
    @InProceedings{laradji19dgpvsi,
    author = {Issam H. Laradji and Mark Schmidt and Vladimir Pavlovic and Minyoung Kim},
    booktitle = {Int'l Joint Conference on Neural Networks {IJCNN}},
    title = {Efficient Deep Gaussian Process Models for Variable-Sized Input},
    year = {2019},
    address = {Budapest, Hungary},
    month = jul,
    date-modified = {2019-09-05 21:26:55 +0100},
    doi = {10.1109/ijcnn.2019.8851768},
    }

  • I. H. Laradji, M. Schmidt, V. Pavlovic, and M. Kim, “Efficient Deep Gaussian Process Models for Variable-Sized Input,” CoRR, vol. abs/1905.06982, 2019. doi:10.1109/ijcnn.2019.8851768
    [BibTeX]
    @Article{laradji19dgpvsi_arxiv,
    author = {Issam H. Laradji and Mark Schmidt and Vladimir Pavlovic and Minyoung Kim},
    journal = {CoRR},
    title = {Efficient Deep Gaussian Process Models for Variable-Sized Input},
    year = {2019},
    volume = {abs/1905.06982},
    doi = {10.1109/ijcnn.2019.8851768},
    }

  • F. Han, R. Guerrero, and V. Pavlovic, “VirtualCook: Cross-modal Synthesis of Food Images from Ingredients,” in Int’l Joint Conference on Artificial Intelligence IJCNN, Workshop on AI and Food, Macao, China, 2019.
    [BibTeX]
    @inproceedings{han19art_ijcai,
    Address = {Macao, China},
    Author = {Fangda Han and Ricardo Guerrero and Vladimir Pavlovic},
    Booktitle = {Int'l Joint Conference on Artificial Intelligence {IJCNN}, Workshop on AI and Food},
    Date-Modified = {2019-09-05 20:50:46 +0100},
    Month = aug,
    Title = {VirtualCook: Cross-modal Synthesis of Food Images from Ingredients},
    Year = {2019}}

  • F. Han, R. Guerrero, and V. Pavlovic, “The Art of Food: Meal Image Synthesis from Ingredients,” CoRR, vol. abs/1905.13149, 2019.
    [BibTeX]
    @Article{han19art_arxiv,
    author = {Fangda Han and Ricardo Guerrero and Vladimir Pavlovic},
    journal = {CoRR},
    title = {The Art of Food: Meal Image Synthesis from Ingredients},
    year = {2019},
    volume = {abs/1905.13149},
    eprint = {1905.13149v1},
    }

2018

  • G. Qiao, S. Yoon, M. Kapadia, and V. Pavlovic, “The Role of Data-Driven Priors in Multi-Agent Crowd Trajectory Estimation,” in AAAI, 2018, p. 4710–4717.
    [BibTeX]
    @inproceedings{gang19priors,
    Author = {Gang Qiao and Sejong Yoon and Mubbasir Kapadia and Vladimir Pavlovic},
    Booktitle = {{AAAI}},
    Pages = {4710--4717},
    Publisher = {{AAAI} Press},
    Title = {The Role of Data-Driven Priors in Multi-Agent Crowd Trajectory Estimation},
    Year = {2018}}

  • H. X. Pham, Y. Wang, and V. Pavlovic, “End-to-end Learning for 3D Facial Animation from Speech,” in ICMI, 2018, p. 361–365. doi:10.1145/3242969.3243017
    [BibTeX]
    @InProceedings{hai18icmi,
    author = {Hai Xuan Pham and Yuting Wang and Vladimir Pavlovic},
    booktitle = {{ICMI}},
    title = {End-to-end Learning for 3D Facial Animation from Speech},
    year = {2018},
    pages = {361--365},
    publisher = {{ACM}},
    doi = {10.1145/3242969.3243017},
    }

  • M. Kim and V. Pavlovic, “Variational Inference for Gaussian Process Models for Survival Analysis,” in UAI, 2018, p. 435–445.
    [BibTeX]
    @inproceedings{kim18uai,
    Author = {Minyoung Kim and Vladimir Pavlovic},
    Booktitle = {{UAI}},
    Pages = {435--445},
    Publisher = {{AUAI} Press},
    Title = {Variational Inference for Gaussian Process Models for Survival Analysis},
    Year = {2018}}

  • H. X. Pham, Y. Wang, and V. Pavlovic, “Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network,” CoRR, vol. abs/1803.07716, 2018.
    [BibTeX]
    @article{hai18gath_arxiv,
    Author = {Hai Xuan Pham and Yuting Wang and Vladimir Pavlovic},
    Journal = {CoRR},
    Title = {Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network},
    Volume = {abs/1803.07716},
    Year = {2018}}

  • B. Gholami, P. Sahu, O. Rudovic, K. Bousmalis, and V. Pavlovic, “Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach,” CoRR, vol. abs/1810.11547, 2018.
    [BibTeX]
    @article{behnam18umtda_arxiv,
    Author = {Behnam Gholami and Pritish Sahu and Ognjen Rudovic and Konstantinos Bousmalis and Vladimir Pavlovic},
    Journal = {CoRR},
    Title = {Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach},
    Volume = {abs/1810.11547},
    Year = {2018}}

2017

  • W. Liu, K. Hu, S. Yoon, V. Pavlovic, P. Faloutsos, and M. Kapadia, “Characterizing the Relationship between Environment Layout and Crowd Movement using Machine Learning,” in Motion in Games (MiG), Barcelona, Spain, 2017. doi:10.1145/3136457.3136474
    [BibTeX]
    @InProceedings{liu17mig,
    author = {Weining Liu and Kaidong Hu and Sejong Yoon and Vladimir Pavlovic and Petros Faloutsos and Mubbasir Kapadia},
    booktitle = {Motion in Games (MiG)},
    title = {Characterizing the Relationship between Environment Layout and Crowd Movement using Machine Learning},
    year = {2017},
    address = {Barcelona, Spain},
    month = nov,
    doi = {10.1145/3136457.3136474},
    keywords = {crowd modeling, deep models},
    }

  • C. D. Tran, O. Rudovic, and V. Pavlovic, “Unsupervised domain adaptation with copula models,” in IEEE Int’l Conf. Machine Learning for Signal Processing (MLSP), 2017. doi:10.1109/mlsp.2017.8168131
    [BibTeX]
    @InProceedings{tran17mlsp,
    author = {Cuong D. Tran and Ognjen Rudovic and Vladimir Pavlovic},
    booktitle = {IEEE Int'l Conf. Machine Learning for Signal Processing (MLSP)},
    title = {Unsupervised domain adaptation with copula models},
    year = {2017},
    note = {33\% contribution.},
    date-added = {2017-01-17 15:43:46 +0000},
    date-modified = {2017-01-17 15:45:08 +0000},
    doi = {10.1109/mlsp.2017.8168131},
    keywords = {domain adaptation, mlsp17},
    }

  • B. Gholami, O. Rudovic, and V. Pavlovic, “PUnDA: Probabilistic Unsupervised Domain Adaptation for Knowledge Transfer Across Visual Categories,” in Int’l Conf. Computer Vision, 2017. doi:10.1109/iccv.2017.387
    [BibTeX]
    @InProceedings{babagholami17iccv,
    author = {Behnam Gholami and Ognjen Rudovic and Vladimir Pavlovic},
    booktitle = {Int'l Conf. Computer Vision},
    title = {PUnDA: Probabilistic Unsupervised Domain Adaptation for Knowledge Transfer Across Visual Categories},
    year = {2017},
    note = {33\% contribution.},
    date-added = {2017-01-17 15:43:46 +0000},
    date-modified = {2017-01-17 15:45:08 +0000},
    doi = {10.1109/iccv.2017.387},
    keywords = {domain adaptation, iccv17},
    }

  • H. Pham and V. Pavlovic, “Speech-driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition – Workshop on Deep Affective Learning and Context Modeling, 2017. doi:10.1109/cvprw.2017.287
    [BibTeX]
    @InProceedings{pham17cvpr,
    author = {Pham, Hai and Pavlovic, Vladimir},
    booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition - Workshop on Deep Affective Learning and Context Modeling},
    title = {Speech-driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach},
    year = {2017},
    doi = {10.1109/cvprw.2017.287},
    keywords = {emotions, face animation, speech, cvpr17},
    }

  • L. Sheng, J. Cai, T. Cham, V. Pavlovic, and K. N. Ngan, “A Generative Model for Depth-based Robust 3D Facial Pose Tracking,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition, 2017. doi:10.1109/cvpr.2017.489
    [BibTeX]
    @InProceedings{sheng17cvpr,
    author = {Lu Sheng and Jianfei Cai and Tat-Jen Cham and Vladimir Pavlovic and King Ngi Ngan},
    booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition},
    title = {A Generative Model for Depth-based Robust 3D Facial Pose Tracking},
    year = {2017},
    note = {25\% contribution.},
    date-added = {2017-01-17 15:45:33 +0000},
    date-modified = {2017-01-17 15:46:47 +0000},
    doi = {10.1109/cvpr.2017.489},
    keywords = {depth camera, face modeling, face tracking, cvpr17},
    }

  • B. Babagholami and V. Pavlovic, “Probabilistic Temporal Subspace Clustering,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition, 2017. doi:10.1109/cvpr.2017.459
    [BibTeX]
    @InProceedings{babagholami17cvpr,
    author = {Behnam Babagholami and Vladimir Pavlovic},
    booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition},
    title = {Probabilistic Temporal Subspace Clustering},
    year = {2017},
    note = {50\% contribution.},
    date-added = {2017-01-17 15:43:46 +0000},
    date-modified = {2017-01-17 15:45:08 +0000},
    doi = {10.1109/cvpr.2017.459},
    keywords = {subspace clustering, cvpr17},
    }

  • R. Walecki, O. Rudovic, V. Pavlovic, and M. Pantic, “Deep Structured Learning for Facial Expression Intensity Estimation,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition, 2017.
    [BibTeX]
    @inproceedings{walecki17cvpr,
    Author = {Robert Walecki and Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    Booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition},
    Date-Added = {2017-01-17 15:41:28 +0000},
    Date-Modified = {2017-01-17 15:43:23 +0000},
    Keywords = {deep learning, emotion modeling, ordinal models, expression intensity estimation, cvpr17},
    Note = {25\% contribution.},
    Title = {Deep Structured Learning for Facial Expression Intensity Estimation},
    Year = {2017}}

  • R. Walecki, O. Rudovic, V. Pavlovic, and M. Pantic, “A Copula Ordinal Regression Framework for Joint Estimation of Facial Action Unit Intensity,” IEEE Trans. Affective Computing, 2017. doi:10.1109/taffc.2017.2728534
    [BibTeX]
    @Article{walecki17tac,
    author = {Robert Walecki and Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    journal = {{IEEE} Trans. Affective Computing},
    title = {A Copula Ordinal Regression Framework for Joint Estimation of Facial Action Unit Intensity},
    year = {2017},
    note = {25\% contribution.},
    date-added = {2017-01-17 15:39:15 +0000},
    date-modified = {2017-01-17 15:40:40 +0000},
    doi = {10.1109/taffc.2017.2728534},
    keywords = {emotion modeling, expression intensity estimation, ordinal models, copula models},
    }

  • R. Mehrizi, X. Xu, S. T. Zhang, V. Pavlovic, D. Metaxas, and K. Li, “Using a Marker-Less Method for Estimating L5/S1 Moments during Symmetrical Lifting Applied Ergonomics,” Applied Ergonomics, p. 541–550, 2017.
    [BibTeX]
    @article{mehrizi17ae,
    Author = {Mehrizi, R. and Xu, X. and Zhang, S. T. and Pavlovic, V. and Metaxas, D. and Li, K.},
    Journal = {Applied Ergonomics},
    Pages = {541--550},
    Title = {Using a Marker-Less Method for Estimating L5/S1 Moments during Symmetrical Lifting Applied Ergonomics},
    Vol = {65},
    Year = {2017}}

  • J. Kim and V. Pavlovic, “Discovering Characteristic Landmarks on Ancient Coins Using Convolutional Networks,” SPIE Journal of Electronic Imaging, 2017. doi:10.1117/1.JEI.26.1.011018
    [BibTeX]
    @article{jongpil16spie,
    Author = {Jongpil Kim and Vladimir Pavlovic},
    Date-Added = {2016-09-11 21:37:27 +0000},
    Date-Modified = {2017-01-17 15:49:38 +0000},
    Doi = {10.1117/1.JEI.26.1.011018},
    Journal = {{SPIE} Journal of Electronic Imaging},
    Keywords = {coin analysis, deep learning},
    Note = {Accepted for publication. 50\% contribution.},
    Title = {Discovering Characteristic Landmarks on Ancient Coins Using Convolutional Networks},
    Year = {2017},
    Bdsk-Url-1 = {https://doi.org/10.1117/1.JEI.26.1.011018}}

  • O. Rudovic, M. Nicolaou, and V. Pavlovic, “Social Signal Processing,” , A. Vinciarelli, J. Burgoon, N. Magnenat-Thalmann, and M. Pantic, Eds., Cambridge University Press, 2017.
    [BibTeX]
    @inbook{rudovic14mlssp,
    Author = {Ognjen Rudovic and Mihalis Nicolaou and Vladimir Pavlovic},
    Chapter = {Machine Learning Methods for Social Signal Processing},
    Editor = {Alessandro Vinciarelli and Judee Burgoon and Nadia Magnenat-Thalmann and Maja Pantic},
    Note = {33\% contribution},
    Publisher = {Cambridge University Press},
    Title = {Social Signal Processing},
    Year = {2017}}

  • H. Pham, S. Cheung, and V. Pavlovic, “Speech-driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition – Workshop on Deep Affective Learning and Context Modeling, 2017. doi:10.1109/cvprw.2017.287
    [BibTeX]
    @InProceedings{Pham2017,
    author = {Hai Pham and Samuel Cheung and Vladimir Pavlovic},
    booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition - Workshop on Deep Affective Learning and Context Modeling},
    title = {Speech-driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach},
    year = {2017},
    doi = {10.1109/cvprw.2017.287},
    keywords = {deep learning, emotion modeling, face animation, speech analysis},
    owner = {vladimir},
    timestamp = {2017.06.19},
    }

  • C. Chen, H. X. Pham, V. Pavlovic, J. Cai, G. Shi, and Y. Gao, “Using 3D Face Priors for Depth Recovery,” J. Visual Commun. Image Represent., 2017. doi:10.1016/j.jvcir.2017.06.002
    [BibTeX]
    @Article{chen17jvcir,
    author = {Chongyu Chen and Hai Xuan Pham and Vladimir Pavlovic and Jianfei Cai and Guangming Shi and Yuefang Gao},
    journal = {J. Visual Commun. Image Represent.},
    title = {Using 3D Face Priors for Depth Recovery},
    year = {2017},
    doi = {10.1016/j.jvcir.2017.06.002},
    owner = {vladimir},
    timestamp = {2017.06.19},
    }

  • L. Zhao, F. Han, M. Kapadia, V. Pavlovic, and D. Metaxas, “Sketch-based Face Editing in Video Using Identity Deformation Transfer,” , 2017.
    [BibTeX] [Abstract]

    We address the problem of using hand-drawn sketch to edit facial identity, such as enlarging the shape or modifying the position of eyes or mouth, in the whole video. This task is formulated as a 3D face model reconstruction and deformation problem. We first introduce a two-stage real-time 3D face model fitting schema to recover facial identity and expressions from the video. We recognize the user’s editing intention from the input sketch as a set of facial modifications. A novel identity deformation algorithm is then proposed to transfer these deformations from 2D space to 3D facial identity directly, while preserving the facial expressions. Finally, these changes are propagated to the whole video with the modified identity. Experimental results demonstrate that our method can effectively edit facial identity in video based on the input sketch with high consistency and fidelity.

    @Electronic{zhao17arx,
    author = {Long Zhao and Fangda Han and Mubbasir Kapadia and Vladimir Pavlovic and Dimitris Metaxas},
    title = {Sketch-based Face Editing in Video Using Identity Deformation Transfer},
    year = {2017},
    abstract = {We address the problem of using hand-drawn sketch to edit facial identity, such as enlarging the shape or modifying the position of eyes or mouth, in the whole video. This task is formulated as a 3D face model reconstruction and deformation problem. We first introduce a two-stage real-time 3D face model fitting schema to recover facial identity and expressions from the video. We recognize the user's editing intention from the input sketch as a set of facial modifications. A novel identity deformation algorithm is then proposed to transfer these deformations from 2D space to 3D facial identity directly, while preserving the facial expressions. Finally, these changes are propagated to the whole video with the modified identity. Experimental results demonstrate that our method can effectively edit facial identity in video based on the input sketch with high consistency and fidelity.},
    date = {2017-03-25},
    eprint = {1703.08738v1},
    eprintclass = {cs.CV},
    eprinttype = {arXiv},
    file = {online:http\:/arxiv.org/pdf/1703.08738v1:PDF},
    keywords = {cs.CV, face animation},
    owner = {vladimir},
    timestamp = {2017.06.19},
    }

  • H. X. Pham, Y. Wang, and V. Pavlovic, End-to-end Learning for 3D Facial Animation from Raw Waveforms of Speech, 2017.
    [BibTeX] [Download PDF]
    @unpublished{pham18fg,
    Author = {Hai Xuan Pham and Yuting Wang and Vladimir Pavlovic},
    Keywords = {emotions, face animation, speech},
    Note = {under review},
    Title = {End-to-end Learning for 3D Facial Animation from Raw Waveforms of Speech},
    Url = {https://arxiv.org/abs/1710.00920},
    Year = {2017},
    Bdsk-Url-1 = {https://arxiv.org/abs/1710.00920}}

  • G. Yang, S. Yoon, M. Kapadia, and V. Pavlovic, The Role of Data-driven Priors in Multi-agent Crowd Trajectory Estimation, 2017.
    [BibTeX]
    @unpublished{yang18aaai,
    Author = {Gang Yang and Sejong Yoon and Mubbasir Kapadia and Vladimir Pavlovic},
    Keywords = {crowd modeling, deep networks, motion priors},
    Note = {under review},
    Title = {The Role of Data-driven Priors in Multi-agent Crowd Trajectory Estimation},
    Year = {2017}}

2016

  • K. Tsourides, S. Shariat, H. Nejati, T. K. Gandhi, A. Cardinaux, C. T. Simons, N. Cheung, V. Pavlovic, and P. Sinha, “Neural correlates of the food/non-food visual distinction,” Biol. Psychol., vol. 115, p. 35–42, 2016. doi:10.1016/j.biopsycho.2015.12.013
    [BibTeX]
    @Article{Tsourides2016bp,
    author = {Tsourides, Kleovoulos and Shariat, Shahriar and Nejati, Hossein and Gandhi, Tapan K and Cardinaux, Annie and Simons, Christopher T and Cheung, Ngai-Man and Pavlovic, Vladimir and Sinha, Pawan},
    journal = {Biol. Psychol.},
    title = {Neural correlates of the food/non-food visual distinction},
    year = {2016},
    month = mar,
    pages = {35--42},
    volume = {115},
    doi = {10.1016/j.biopsycho.2015.12.013},
    keywords = {Edibility; Image representation; Likability; MEG; Machine learning; Visual distinction},
    }

  • S. Yoon and V. Pavlovic, “Decentralized Probabilistic Learning For Sensor Networks,” in IEEE Global Conference on Signal and Information Processing, 2016.
    [BibTeX]
    @inproceedings{yoon16gsip,
    Author = {Sejong Yoon and Vladimir Pavlovic},
    Booktitle = {IEEE Global Conference on Signal and Information Processing},
    Date-Added = {2016-09-11 21:34:27 +0000},
    Date-Modified = {2016-09-11 21:35:57 +0000},
    Month = dec,
    Note = {50\% contribution.},
    Title = {Decentralized Probabilistic Learning For Sensor Networks},
    Year = {2016}}

  • H. X. Pham and V. Pavlovic, “Robust Real-Time 3D Face Tracking from RGBD Videos under Extreme Pose, Depth, and Expression Variations,” in Proc. Intl. Conf. on 3D Vision (3DV), Stanford University, CA, 2016. doi:10.1109/3dv.2016.54
    [BibTeX]
    @InProceedings{pham163dv,
    author = {Hai Xuan Pham and Vladimir Pavlovic},
    booktitle = {Proc. Intl. Conf. on 3D Vision (3DV)},
    title = {Robust Real-Time 3D Face Tracking from RGBD Videos under Extreme Pose, Depth, and Expression Variations},
    year = {2016},
    address = {Stanford University, CA},
    month = oct,
    note = {50\% contribution.},
    date-added = {2016-09-11 21:31:16 +0000},
    date-modified = {2016-09-11 21:33:15 +0000},
    doi = {10.1109/3dv.2016.54},
    }

  • H. X. Pham, V. Pavlovic, J. Cai, and T. Cham, “Robust Real-time Performance-driven 3D Face Tracking,” in Proc. Intl. Conf. Pattern Recognition (ICPR), Cancun, Mexico, 2016. doi:10.1109/icpr.2016.7899906
    [BibTeX]
    @InProceedings{pham16icpr,
    author = {Hai Xuan Pham and Vladimir Pavlovic and Jianfei Cai and Tat-Jen Cham},
    booktitle = {Proc. Intl. Conf. Pattern Recognition ({ICPR})},
    title = {Robust Real-time Performance-driven 3D Face Tracking},
    year = {2016},
    address = {Cancun, Mexico},
    month = dec,
    note = {25\% contribution.},
    date-added = {2016-09-11 21:30:00 +0000},
    date-modified = {2016-09-11 21:31:09 +0000},
    doi = {10.1109/icpr.2016.7899906},
    }

  • J. Kim and V. Pavlovic, “Discovering Characteristic Landmarks on Ancient Coins Using Convolutional Networks,” in Proc. Intl. Conf. Pattern Recognition (ICPR), Cancun, Mexico, 2016. doi:10.1117/1.jei.26.1.011018
    [BibTeX]
    @InProceedings{jongpil16icpr_coin,
    author = {Jongpil Kim and Vladimir Pavlovic},
    booktitle = {Proc. Intl. Conf. Pattern Recognition ({ICPR})},
    title = {Discovering Characteristic Landmarks on Ancient Coins Using Convolutional Networks},
    year = {2016},
    address = {Cancun, Mexico},
    month = dec,
    note = {50\% contribution.},
    date-added = {2016-09-11 21:28:58 +0000},
    date-modified = {2016-09-11 21:29:55 +0000},
    doi = {10.1117/1.jei.26.1.011018},
    keywords = {coin analysis, deep learning},
    }

  • J. Kim and V. Pavlovic, “A Shape Preserving Approach for Salient Object Detection Using Convolutional Neural Networks,” in Proc. Intl. Conf. Pattern Recognition (ICPR), Cancun, Mexico, 2016. doi:10.1109/icpr.2016.7899701
    [BibTeX]
    @InProceedings{jongpil16icpr,
    author = {Jongpil Kim and Vladimir Pavlovic},
    booktitle = {Proc. Intl. Conf. Pattern Recognition ({ICPR})},
    title = {A Shape Preserving Approach for Salient Object Detection Using Convolutional Neural Networks},
    year = {2016},
    address = {Cancun, Mexico},
    month = dec,
    note = {50\% contribution.},
    date-added = {2016-09-11 21:27:37 +0000},
    date-modified = {2016-09-11 21:28:50 +0000},
    doi = {10.1109/icpr.2016.7899701},
    }

  • J. Kim and V. Pavlovic, “A Shape-based Approach for Saliency Object Detection using Deep Learning,” in Proc. European Conf. Computer Vision, 2016. doi:10.1007/978-3-319-46493-0_28
    [BibTeX]
    @InProceedings{jongpil16eccv,
    author = {Jongpil Kim and Vladimir Pavlovic},
    booktitle = {Proc. European Conf. Computer Vision},
    title = {A Shape-based Approach for Saliency Object Detection using Deep Learning},
    year = {2016},
    month = oct,
    note = {50\% contribution.},
    date-added = {2016-09-11 21:25:41 +0000},
    date-modified = {2016-09-11 21:27:29 +0000},
    doi = {10.1007/978-3-319-46493-0_28},
    }

  • R. Walecki, O. Rudovic, M. Pantic, V. Pavlovic, and J. F. Cohn, “A Framework for Joint Estimation and Guided Annotation of Facial Action Unit Intensity,” in Proc. of IEEE Int’l Conf. Computer Vision and Pattern Recognition (CVPR’W 2016), Las Vegas, NV, 2016. doi:10.1109/cvprw.2016.183
    [BibTeX]
    @InProceedings{walecki16cvprws,
    author = {R. Walecki and O. Rudovic and M. Pantic and V. Pavlovic and J. F. Cohn},
    booktitle = {Proc. of {IEEE} Int'l Conf. Computer Vision and Pattern Recognition (CVPR'W 2016)},
    title = {A Framework for Joint Estimation and Guided Annotation of Facial Action Unit Intensity},
    year = {2016},
    address = {Las Vegas, NV},
    month = jun,
    note = {25\% contribution.},
    date-added = {2016-09-11 21:20:12 +0000},
    date-modified = {2016-09-11 21:22:09 +0000},
    doi = {10.1109/cvprw.2016.183},
    keywords = {emotion modeling, ordinal models, expression intensity estimation, conditional ordinal random field},
    }

  • R. Walecki, O. Rudovic, V. Pavlovic, and M. Pantic, “Variable-state Latent Conditional Random Field Models for Facial Expression Analysis,” Image and Vision Computing, 2016. doi:10.1016/j.imavis.2016.04.009
    [BibTeX]
    @Article{walecki16imavis,
    author = {R. Walecki and O. Rudovic and V. Pavlovic and M. Pantic},
    journal = {Image and Vision Computing},
    title = {Variable-state Latent Conditional Random Field Models for Facial Expression Analysis},
    year = {2016},
    note = {25\% contribution.},
    date-added = {2016-09-11 21:18:32 +0000},
    date-modified = {2016-09-11 21:19:22 +0000},
    doi = {10.1016/j.imavis.2016.04.009},
    keywords = {emotion modeling, ordinal models, expression intensity estimation},
    }

  • J. Kim and V. Pavlovic, “A Shape Based Approach for Salient Object Detection Using Convolutional Networks,” in arXiv, 2016.
    [BibTeX]
    @inproceedings{jongpil16cvpr,
    Author = {Jongpil Kim and Vladimir Pavlovic},
    Booktitle = {arXiv},
    Date-Added = {2016-02-18 13:47:55 +0000},
    Date-Modified = {2016-02-18 13:48:38 +0000},
    Note = {50\% contribution.},
    Title = {A Shape Based Approach for Salient Object Detection Using Convolutional Networks},
    Year = {2016}}

  • S. Yoon, M. Kapadia, P. Sahu, and V. Pavlovic, “Filling in the Blanks: Reconstructing Microscopic Crowd Motion from Multiple Disparate Noisy Sensors,” in 2016 IEEE Winter Applications of Computer Vision Workshops, WACV 2016 Workshops, 2016, p. 1–9. doi:10.1109/wacvw.2016.7470118
    [BibTeX]
    @InProceedings{yoon16wacvws,
    author = {Sejong Yoon and Mubbasir Kapadia and Pritish Sahu and Vladimir Pavlovic},
    booktitle = {2016 {IEEE} Winter Applications of Computer Vision Workshops, {WACV} 2016 Workshops},
    title = {Filling in the Blanks: Reconstructing Microscopic Crowd Motion from Multiple Disparate Noisy Sensors},
    year = {2016},
    month = mar,
    note = {25\% contribution.},
    pages = {1--9},
    date-added = {2016-02-18 13:43:36 +0000},
    date-modified = {2016-09-11 21:17:46 +0000},
    doi = {10.1109/wacvw.2016.7470118},
    }

  • B. Babagholami, S. Yoon, and V. Pavlovic, “D-MFVI: Distributed Mean Field Variational Inference using Bregman ADMM,” in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, Phoenix, Arizona, {USA.}, 2016, p. 1582–158.
    [BibTeX]
    @InProceedings{behnam16aaai,
    author = {Behnam Babagholami and Sejong Yoon and Vladimir Pavlovic},
    booktitle = {Proceedings of the Thirtieth {AAAI} Conference on Artificial Intelligence},
    title = {{D-MFVI}: Distributed Mean Field Variational Inference using Bregman {ADMM}},
    year = {2016},
    address = {Phoenix, Arizona, {USA.}},
    month = feb,
    note = {33\% contribution},
    pages = {1582--158},
    bdsk-url-1 = {http://arxiv.org/abs/1507.00824},
    date-modified = {2016-09-11 21:16:12 +0000},
    eprint = {1507.00824},
    eprinttype = {arxiv},
    }

  • R. Walecki, O. Rudovic, V. Pavlovic, and M. Pantic, “Copula Ordinal Regression for Joint Intensity Estimation of Facial Action Units,” in Proc. of IEEE Int’l Conf. Computer Vision and Pattern Recognition (CVPR’W 2016), Las Vegas, NV, 2016.
    [BibTeX]
    @inproceedings{walecki16cvpr,
    Address = {Las Vegas, NV},
    Author = {Robert Walecki and Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    Booktitle = {Proc. of {IEEE} Int'l Conf. Computer Vision and Pattern Recognition (CVPR'W 2016)},
    Date-Modified = {2016-09-11 21:21:55 +0000},
    Keywords = {emotion modeling, ordinal models, expression intensity estimation, copula models},
    Month = jun,
    Note = {25\% contribution},
    Title = {Copula Ordinal Regression for Joint Intensity Estimation of Facial Action Units},
    Year = {2016}}

  • C. Song, S. Yoon, and V. Pavlovic, “Fast ADMM Algorithm for Distributed Optimization with Adaptive Penalty,” in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, Phoenix, Arizona, {USA.}, 2016, p. 753–759.
    [BibTeX]
    @InProceedings{yoon16aaai,
    author = {Changkyu Song and Sejong Yoon and Vladimir Pavlovic},
    booktitle = {Proceedings of the Thirtieth {AAAI} Conference on Artificial Intelligence},
    title = {Fast {ADMM} Algorithm for Distributed Optimization with Adaptive Penalty},
    year = {2016},
    address = {Phoenix, Arizona, {USA.}},
    month = feb,
    note = {33\% contribution},
    pages = {753--759},
    bdsk-url-1 = {http://arxiv.org/abs/1506.08928},
    date-modified = {2016-09-11 21:16:22 +0000},
    eprint = {1506.08928},
    eprinttype = {arxiv},
    }

2015

  • C. Dalal, V. Pavlovic, and R. Kopp, “Sea-Level Estimation using the Riemannian Manifold and a Non-stationary Covariance Function,” in Proc. Climate Informatics 2015, 2015.
    [BibTeX]
    @inproceedings{dalal15ciw,
    Author = {Chintan Dalal and Vladimir Pavlovic and Robert Kopp},
    Booktitle = {Proc. Climate Informatics 2015},
    Date-Added = {2015-10-17 12:07:45 +0000},
    Date-Modified = {2015-10-17 12:08:57 +0000},
    Note = {33\% contribution},
    Title = {Sea-Level Estimation using the Riemannian Manifold and a Non-stationary Covariance Function},
    Year = {2015}}

  • H. X. Pham, C. Chen, L. D. Nguyen, V. Pavlovic, J. Cai, and T. Cham, “Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes,” International Journal of Computer Vision, 2015.
    [BibTeX]
    @article{pham15ijcv,
    Author = {Hai Xuan Pham and Chongyu Chen and Luc Dao Nguyen and Vladimir Pavlovic and Jianfei Cai and Tat-Jen Cham},
    Date-Added = {2015-10-17 12:05:43 +0000},
    Date-Modified = {2015-10-17 12:06:50 +0000},
    Journal = {International Journal of Computer Vision},
    Note = {under review; 25\% contribution},
    Title = {Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes},
    Year = {2015}}

  • C. Dalal, V. Pavlovic, and R. Kopp, “Intrinsic Non-stationary Covariance Function for Climate Modeling,” in arXiv, 2015.
    [BibTeX]
    @InProceedings{dalal15nips,
    author = {Chintan Dalal and Vladimir Pavlovic and Robert Kopp},
    booktitle = {arXiv},
    title = {Intrinsic Non-stationary Covariance Function for Climate Modeling},
    year = {2015},
    note = {33\% contribution},
    bdsk-url-1 = {http://arxiv.org/abs/1507.02356},
    eprint = {1507.02356},
    eprinttype = {arxiv},
    }

  • J. Kim and V. Pavlovic, “Discovering Characteristic Landmarks on Ancient Coins using Convolutional Networks,” in arXiv, 2015. doi:10.1117/1.jei.26.1.011018
    [BibTeX]
    @InProceedings{kim15iccv,
    author = {Jongpil Kim and Vladimir Pavlovic},
    booktitle = {arXiv},
    title = {Discovering Characteristic Landmarks on Ancient Coins using Convolutional Networks},
    year = {2015},
    note = {50\% contribution},
    bdsk-url-1 = {http://arxiv.org/abs/1506.09174},
    doi = {10.1117/1.jei.26.1.011018},
    eprint = {1506.09174},
    eprinttype = {arxiv},
    keywords = {coin analysis, deep learning},
    }

  • H. Pham, L. D. Nguyen, V. Pavlovic, J. Cai, C. Chen, and T. Cham, “Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes,” in arXiv, 2015.
    [BibTeX]
    @InProceedings{pham15iccv,
    author = {Hai Pham and Luc Dao Nguyen and Vladimir Pavlovic and Jianfei Cai and Chongyu Chen and Tat-Jen Cham},
    booktitle = {arXiv},
    title = {Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes},
    year = {2015},
    note = {25\% contribution},
    bdsk-url-1 = {http://arxiv.org/abs/1507.02779},
    eprint = {1507.02779},
    eprinttype = {arxiv},
    }

  • C. Tran, V. Pavlovic, and R. Kopp, “Gaussian Process for Noisy Inputs with Ordering Constraints,” in arXiv, 2015.
    [BibTeX]
    @InProceedings{tran15nips,
    author = {Cuong Tran and Vladimir Pavlovic and Robert Kopp},
    booktitle = {arXiv},
    title = {Gaussian Process for Noisy Inputs with Ordering Constraints},
    year = {2015},
    note = {33\% contribution},
    bdsk-url-1 = {http://arxiv.org/abs/1507.00052},
    eprint = {1507.00052},
    eprinttype = {arxiv},
    }

  • R. Walecki, O. Rudovic, V. Pavlovic, and M. Pantic, “Variable-state Latent Conditional Random Fields for Facial Expression Recognition and Action Unit Detection,” in Proc. of IEEE International Conference on Automatic Face and Gesture Recognition, 2015, p. 1–8. doi:10.1109/fg.2015.7163137
    [BibTeX]
    @InProceedings{walecki15fg,
    author = {Robert Walecki and Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    booktitle = {Proc. of {IEEE} International Conference on Automatic Face and Gesture Recognition},
    title = {Variable-state Latent Conditional Random Fields for Facial Expression Recognition and Action Unit Detection},
    year = {2015},
    month = may,
    note = {25\% contribution; oral},
    pages = {1--8},
    doi = {10.1109/fg.2015.7163137},
    keywords = {emotion modeling, ordinal models, expression intensity estimation, conditional ordinal random field},
    }

  • S. Yi and V. Pavlovic, “Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation,” in Intl Conference on Computer Vision, 2015. doi:10.1109/iccv.2015.373
    [BibTeX]
    @InProceedings{yi15iccv,
    author = {Saehoon Yi and Vladimir Pavlovic},
    booktitle = {Intl Conference on Computer Vision},
    title = {Multi-Cue Structure Preserving {MRF} for Unconstrained Video Segmentation},
    year = {2015},
    note = {50\% contribution},
    bdsk-url-1 = {http://arxiv.org/abs/1506.09124},
    doi = {10.1109/iccv.2015.373},
    eprint = {1506.09124},
    eprinttype = {arxiv},
    }

  • O. Rudovic, V. Pavlovic, and M. Pantic, “Context-Sensitive Dynamic Ordinal Regression for Intensity Estimation of Facial Action Units,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 37, iss. 5, p. 944–958, 2015. doi:10.1109/TPAMI.2014.2356192
    [BibTeX]
    @Article{rudovic15pami,
    author = {Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    journal = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
    title = {Context-Sensitive Dynamic Ordinal Regression for Intensity Estimation of Facial Action Units},
    year = {2015},
    note = {33\% contribution},
    number = {5},
    pages = {944--958},
    volume = {37},
    bdsk-url-1 = {http://dx.doi.org/10.1109/TPAMI.2014.2356192},
    doi = {10.1109/TPAMI.2014.2356192},
    }

  • W. Yan, X. Han, and V. Pavlovic, “Structural Learning for Multiple Object Tracking,” Image and Vision Computing, 2015.
    [BibTeX]
    @article{wang15imavis,
    Author = {Wang Yan and Xiaoye Han and Vladimir Pavlovic},
    Date-Added = {2015-06-30 15:31:57 +0000},
    Date-Modified = {2015-06-30 15:37:05 +0000},
    Journal = {Image and Vision Computing},
    Note = {Under review. 33\% contribution.},
    Title = {Structural Learning for Multiple Object Tracking},
    Year = {2015}}

2014

  • C. Chen, H. X. Pham, V. Pavlovic, J. Cai, and G. Shi, “Depth Recovery with Face Priors,” in Computer Vision – ACCV 2014 – 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part IV, 2014, p. 336–351. doi:10.1007/978-3-319-16817-3_22
    [BibTeX]
    @InProceedings{chongyu2014accv,
    author = {Chongyu Chen and Hai Xuan Pham and Vladimir Pavlovic and Jianfei Cai and Guangming Shi},
    booktitle = {Computer Vision - {ACCV} 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part {IV}},
    title = {Depth Recovery with Face Priors},
    year = {2014},
    note = {20\% contribution},
    pages = {336--351},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-319-16817-3_22},
    doi = {10.1007/978-3-319-16817-3_22},
    }

  • J. Kim and V. Pavlovic, “Improving Ancient Roman Coin Recognition with Alignment and Spatial Encoding,” in Computer Vision – ECCV 2014 Workshops – Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part I, 2014, p. 149–164. doi:10.1007/978-3-319-16178-5_10
    [BibTeX]
    @InProceedings{kim2014a,
    author = {Jongpil Kim and Vladimir Pavlovic},
    booktitle = {Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {I}},
    title = {Improving Ancient Roman Coin Recognition with Alignment and Spatial Encoding},
    year = {2014},
    note = {50\% contribution},
    pages = {149--164},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-319-16178-5_10},
    doi = {10.1007/978-3-319-16178-5_10},
    keywords = {coin analysis},
    }

  • J. Kim and V. Pavlovic, “Ancient Coin Recognition Based on Spatial Coding,” in 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, August 24-28, 2014, 2014, p. 321–326. doi:10.1109/ICPR.2014.64
    [BibTeX]
    @InProceedings{kim2014b,
    author = {Jongpil Kim and Vladimir Pavlovic},
    booktitle = {22nd International Conference on Pattern Recognition, {ICPR} 2014, Stockholm, Sweden, August 24-28, 2014},
    title = {Ancient Coin Recognition Based on Spatial Coding},
    year = {2014},
    note = {50\% contribution},
    pages = {321--326},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICPR.2014.64},
    doi = {10.1109/ICPR.2014.64},
    keywords = {coin analysis},
    }

  • H. X. Pham and V. Pavlovic, “Hybrid On-Line 3D Face and Facial Actions Tracking in RGBD Video Sequences,” in 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, August 24-28, 2014, 2014, p. 4194–4199. doi:10.1109/ICPR.2014.719
    [BibTeX]
    @InProceedings{pham2014a,
    author = {Hai Xuan Pham and Vladimir Pavlovic},
    booktitle = {22nd International Conference on Pattern Recognition, {ICPR} 2014, Stockholm, Sweden, August 24-28, 2014},
    title = {Hybrid On-Line 3D Face and Facial Actions Tracking in {RGBD} Video Sequences},
    year = {2014},
    note = {50\% contribution},
    pages = {4194--4199},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICPR.2014.719},
    doi = {10.1109/ICPR.2014.719},
    }

  • S. Yang, O. Rudovic, V. Pavlovic, and M. Pantic, “Personalized Modeling of Facial Action Unit Intensity,” in Advances in Visual Computing – 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, Part II, 2014, p. 269–281. doi:10.1007/978-3-319-14364-4_26
    [BibTeX]
    @InProceedings{rudovic2014icvs,
    author = {Shuang Yang and Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    booktitle = {Advances in Visual Computing - 10th International Symposium, {ISVC} 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, Part {II}},
    title = {Personalized Modeling of Facial Action Unit Intensity},
    year = {2014},
    note = {25\% contribution},
    pages = {269--281},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-319-14364-4_26},
    doi = {10.1007/978-3-319-14364-4_26},
    }

  • S. Yi, P. W. Mirowski, T. K. Ho, and V. Pavlovic, “Pose Invariant Activity Classification for Multi-floor Indoor Localization,” in 22nd International Conference on Pattern Recognition, ICPR 2014, Stockholm, Sweden, August 24-28, 2014, 2014, p. 3505–3510. doi:10.1109/ICPR.2014.603
    [BibTeX]
    @InProceedings{yi14icpr,
    author = {Saehoon Yi and Piotr W. Mirowski and Tin Kam Ho and Vladimir Pavlovic},
    booktitle = {22nd International Conference on Pattern Recognition, {ICPR} 2014, Stockholm, Sweden, August 24-28, 2014},
    title = {Pose Invariant Activity Classification for Multi-floor Indoor Localization},
    year = {2014},
    note = {25\% contribution},
    pages = {3505--3510},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICPR.2014.603},
    doi = {10.1109/ICPR.2014.603},
    }

  • S. Yoon and V. Pavlovic, “Sentiment Flow for Video Interestingness Prediction,” in Proceedings of the 1st ACM International Workshop on Human Centered Event Understanding from Multimedia, New York, NY, USA, 2014, p. 29–34. doi:10.1145/2660505.2660513
    [BibTeX]
    @InProceedings{yoon2014,
    author = {Yoon, Sejong and Pavlovic, Vladimir},
    booktitle = {Proceedings of the 1st ACM International Workshop on Human Centered Event Understanding from Multimedia},
    title = {Sentiment Flow for Video Interestingness Prediction},
    year = {2014},
    address = {New York, NY, USA},
    note = {50\% contribution},
    pages = {29--34},
    publisher = {ACM},
    series = {HuEvent '14},
    bdsk-url-1 = {http://doi.acm.org/10.1145/2660505.2660513},
    bdsk-url-2 = {http://dx.doi.org/10.1145/2660505.2660513},
    doi = {10.1145/2660505.2660513},
    isbn = {978-1-4503-3120-3},
    location = {Orlando, Florida, USA},
    numpages = {6},
    }

  • M. A. Nicolaou, V. Pavlovic, and M. Pantic, “Dynamic Probabilistic CCA for Analysis of Affective Behavior and Fusion of Continuous Annotations,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, iss. 7, p. 1299–1311, 2014. doi:10.1109/TPAMI.2014.16
    [BibTeX]
    @Article{nicolaou14pami,
    author = {Mihalis A. Nicolaou and Vladimir Pavlovic and Maja Pantic},
    journal = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
    title = {Dynamic Probabilistic {CCA} for Analysis of Affective Behavior and Fusion of Continuous Annotations},
    year = {2014},
    note = {33\% contribution},
    number = {7},
    pages = {1299--1311},
    volume = {36},
    bdsk-url-1 = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2014.16},
    bdsk-url-2 = {http://dx.doi.org/10.1109/TPAMI.2014.16},
    doi = {10.1109/TPAMI.2014.16},
    }

  • S. Shariat and V. Pavlovic, “Robust Time-Series Retrieval Using Probabilistic Adaptive Segmental Alignment,” Knowledge and Information Systems, 2014. doi:10.1007/s10115-015-0898-4
    [BibTeX]
    @Article{shariat14kais,
    author = {Shahriar Shariat and Vladimir Pavlovic},
    journal = {Knowledge and Information Systems},
    title = {Robust Time-Series Retrieval Using Probabilistic Adaptive Segmental Alignment},
    year = {2014},
    note = {accepted. 50\% contribution.},
    date-modified = {2015-06-30 15:39:40 +0000},
    doi = {10.1007/s10115-015-0898-4},
    }

2013

  • J. Hu, H. Zhang, A. Miliou, T. Tsimpidis, H. Thornton, and V. Pavlovic, “Categorization of Underwater Habitats Using Dynamic Video Textures,” in Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on, 2013, p. 838–843. doi:10.1109/ICCVW.2013.115
    [BibTeX]
    @inproceedings{hu13iccv,
    Author = {Jun Hu and Han Zhang and Miliou, A. and Tsimpidis, T. and Thornton, H. and Pavlovic, V.},
    Booktitle = {Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on},
    Doi = {10.1109/ICCVW.2013.115},
    Month = dec,
    Note = {33\% contribution},
    Pages = {838--843},
    Title = {Categorization of Underwater Habitats Using Dynamic Video Textures},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICCVW.2013.115}}

  • J. Kim, S. Yoon, and V. Pavlovic, “Relative spatial features for image memorability,” in ACM Multimedia Conference, MM ’13, Barcelona, Spain, October 21-25, 2013, 2013, p. 761–764. doi:10.1145/2502081.2502198
    [BibTeX]
    @InProceedings{kim2013,
    author = {Jongpil Kim and Sejong Yoon and Vladimir Pavlovic},
    booktitle = {{ACM} Multimedia Conference, {MM} '13, Barcelona, Spain, October 21-25, 2013},
    title = {Relative spatial features for image memorability},
    year = {2013},
    note = {33\% contribution},
    pages = {761--764},
    bdsk-url-1 = {http://doi.acm.org/10.1145/2502081.2502198},
    bdsk-url-2 = {http://dx.doi.org/10.1145/2502081.2502198},
    bibsource = {dblp computer science bibliography, http://dblp.org},
    biburl = {http://dblp.uni-trier.de/rec/bib/conf/mm/KimYP13},
    doi = {10.1145/2502081.2502198},
    timestamp = {Fri, 25 Oct 2013 08:31:42 +0200},
    }

  • O. Rudovic, V. Pavlovic, and M. Pantic, “Context-Sensitive Conditional Ordinal Random Fields for Facial Action Intensity Estimation,” in Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on, 2013, p. 492–499. doi:10.1109/ICCVW.2013.70
    [BibTeX]
    @inproceedings{rudovic13iccv,
    Author = {Rudovic, O. and Pavlovic, V. and Pantic, M.},
    Booktitle = {Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on},
    Doi = {10.1109/ICCVW.2013.70},
    Month = dec,
    Note = {33\% contribution},
    Pages = {492--499},
    Title = {Context-Sensitive Conditional Ordinal Random Fields for Facial Action Intensity Estimation},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICCVW.2013.70}}

  • O. Rudovic, V. Pavlovic, and M. Pantic, “Automatic Pain Intensity Estimation with Heteroscedastic Conditional Ordinal Random Fields,” in Advances in Visual Computing – 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II, 2013, p. 234–243. doi:10.1007/978-3-642-41939-3_23
    [BibTeX]
    @InProceedings{rudovic13isvc,
    author = {Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    booktitle = {Advances in Visual Computing - 9th International Symposium, {ISVC} 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part {II}},
    title = {Automatic Pain Intensity Estimation with Heteroscedastic Conditional Ordinal Random Fields},
    year = {2013},
    note = {33\% contribution},
    pages = {234--243},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-642-41939-3_23},
    doi = {10.1007/978-3-642-41939-3_23},
    }

  • S. Shariat and V. Pavlovic, “A New Adaptive Segmental Matching Measure for Human Activity Recognition,” in IEEE International Conference on Computer Vision, ICCV 2013, Sydney, Australia, December 1-8, 2013, 2013, p. 3583–3590. doi:10.1109/ICCV.2013.445
    [BibTeX]
    @InProceedings{shariat13iccv,
    author = {Shahriar Shariat and Vladimir Pavlovic},
    booktitle = {{IEEE} International Conference on Computer Vision, {ICCV} 2013, Sydney, Australia, December 1-8, 2013},
    title = {A New Adaptive Segmental Matching Measure for Human Activity Recognition},
    year = {2013},
    note = {50\% contribution},
    pages = {3583--3590},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICCV.2013.445},
    doi = {10.1109/ICCV.2013.445},
    }

  • S. Yi and V. Pavlovic, “Spatio-temporal Context Modeling for BoW-Based Video Classification,” in Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on, 2013, p. 779–786. doi:10.1109/ICCVW.2013.107
    [BibTeX]
    @inproceedings{yi13iccv,
    Author = {Saehoon Yi and Pavlovic, V.},
    Booktitle = {Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on},
    Doi = {10.1109/ICCVW.2013.107},
    Month = dec,
    Note = {50\% contribution},
    Pages = {779--786},
    Title = {Spatio-temporal Context Modeling for BoW-Based Video Classification},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICCVW.2013.107}}

2012

  • S. Yoon and V. Pavlovic, “Distributed Probabilistic Learning for Camera Networks,” Rutgers, DCS-TR-696, 2012.
    [BibTeX] [Abstract]

    Probabilistic approaches to computer vision typically assume a centralized setting, with the algorithm granted access to all observed data points. However, many problems in wide-area surveillance can bene t from distributed modeling, either because of physical or computations constraints. In this work we present an approach to estimation and learning of generative probabilistic models in a distributed context. In particular, we show how traditional centralized models, such as probabilistic principal component analysis (PPCA), can be learned when the data is distributed across a network of sensors. We demonstrate the utility of this approach on the problem of distributed ane structure from motion (SfM). Our experiments suggest that the accuracy of the accuracy of the learned probabilistic structure and motion models rivals that of traditional centralized factorization methods.

    @techreport{yoon2012a,
    Abstract = {Probabilistic approaches to computer vision typically assume a centralized setting, with the algorithm granted access to all observed data points. However, many problems in wide-area surveillance can benet from distributed modeling, either because of physical or computations constraints. In this work we present an approach to estimation and learning of generative probabilistic models in a distributed context. In
    particular, we show how traditional centralized models, such as probabilistic principal component analysis (PPCA), can be learned when the data is distributed across a network of sensors. We demonstrate the utility of this approach on the problem of distributed ane structure from motion (SfM). Our experiments suggest that the accuracy of the accuracy of the learned probabilistic structure and motion models rivals that of traditional centralized factorization methods.},
    Author = {Yoon, Sejong and Pavlovic, Vladimir},
    Date-Added = {2012-12-07 20:09:22 +0000},
    Date-Modified = {2012-12-07 20:09:22 +0000},
    Institution = {Rutgers},
    Month = jun,
    Note = {50\% contribution},
    Number = {DCS-TR-696},
    Title = {{D}istributed {P}robabilistic {L}earning for {C}amera {N}etworks},
    Year = {2012}}

  • C. Hendahewa and V. Pavlovic, “Analysis of Causality in Stock Market Data,” in 11th International Conference on Machine Learning and Applications, ICMLA, Boca Raton, FL, USA, December 12-15, 2012. Volume 1, 2012, p. 288–293. doi:10.1109/ICMLA.2012.56
    [BibTeX]
    @InProceedings{hendahewa12,
    author = {Chathra Hendahewa and Vladimir Pavlovic},
    booktitle = {11th International Conference on Machine Learning and Applications, ICMLA, Boca Raton, FL, USA, December 12-15, 2012. Volume 1},
    title = {Analysis of Causality in Stock Market Data},
    year = {2012},
    note = {50\% contribution},
    pages = {288--293},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICMLA.2012.56},
    doi = {10.1109/ICMLA.2012.56},
    }

  • J. Kim and V. Pavlovic, “Attribute rating for classification of visual objects,” in Proceedings of the 21st International Conference on Pattern Recognition, ICPR 2012, Tsukuba, Japan, November 11-15, 2012, 2012, p. 1611–1614.
    [BibTeX] [Download PDF]
    @inproceedings{kim2012icpr,
    Author = {Jongpil Kim and Vladimir Pavlovic},
    Booktitle = {Proceedings of the 21st International Conference on Pattern Recognition, {ICPR} 2012, Tsukuba, Japan, November 11-15, 2012},
    Note = {50\% contribution},
    Pages = {1611--1614},
    Title = {Attribute rating for classification of visual objects},
    Url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6460454},
    Year = {2012},
    Bdsk-Url-1 = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6460454}}

  • P. P. Kuksa and V. Pavlovic, “Efficient evaluation of large sequence kernels,” in The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’12, Beijing, China, August 12-16, 2012, 2012, p. 759–767. doi:10.1145/2339530.2339649
    [BibTeX]
    @InProceedings{kuksa12kdd,
    author = {Pavel P. Kuksa and Vladimir Pavlovic},
    booktitle = {The 18th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining, {KDD} '12, Beijing, China, August 12-16, 2012},
    title = {Efficient evaluation of large sequence kernels},
    year = {2012},
    note = {50\% contribution},
    pages = {759--767},
    bdsk-url-1 = {http://doi.acm.org/10.1145/2339530.2339649},
    bdsk-url-2 = {http://dx.doi.org/10.1145/2339530.2339649},
    doi = {10.1145/2339530.2339649},
    }

  • P. P. Kuksa, I. Khan, and V. Pavlovic, “Generalized Similarity Kernels for Efficient Sequence Classification,” in Proceedings of the Twelfth SIAM International Conference on Data Mining, Anaheim, California, USA, April 26-28, 2012., 2012, p. 873–882. doi:10.1137/1.9781611972825.75
    [BibTeX]
    @InProceedings{kuksa12sdm,
    author = {Pavel P. Kuksa and Imdadullah Khan and Vladimir Pavlovic},
    booktitle = {Proceedings of the Twelfth {SIAM} International Conference on Data Mining, Anaheim, California, USA, April 26-28, 2012.},
    title = {Generalized Similarity Kernels for Efficient Sequence Classification},
    year = {2012},
    note = {33\% contribution},
    pages = {873--882},
    bdsk-url-1 = {http://dx.doi.org/10.1137/1.9781611972825.75},
    doi = {10.1137/1.9781611972825.75},
    }

  • M. A. Nicolaou, V. Pavlovic, and M. Pantic, “Dynamic Probabilistic CCA for Analysis of Affective Behaviour,” in Computer Vision – ECCV 2012 – 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part VII, 2012, p. 98–111. doi:10.1007/978-3-642-33786-4_8
    [BibTeX]
    @InProceedings{nicolaou12eccv,
    author = {Mihalis A. Nicolaou and Vladimir Pavlovic and Maja Pantic},
    booktitle = {Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}},
    title = {Dynamic Probabilistic {CCA} for Analysis of Affective Behaviour},
    year = {2012},
    note = {33\% contribution},
    pages = {98--111},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-642-33786-4_8},
    doi = {10.1007/978-3-642-33786-4_8},
    }

  • O. Rudovic, V. Pavlovic, and M. Pantic, “Multi-output Laplacian dynamic ordinal regression for facial expression recognition and intensity estimation,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA, June 16-21, 2012, 2012, p. 2634–2641. doi:10.1109/CVPR.2012.6247983
    [BibTeX]
    @InProceedings{rudovic12cvpr,
    author = {Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    booktitle = {2012 {IEEE} Conference on Computer Vision and Pattern Recognition, Providence, RI, USA, June 16-21, 2012},
    title = {Multi-output Laplacian dynamic ordinal regression for facial expression recognition and intensity estimation},
    year = {2012},
    note = {33\% contribution},
    pages = {2634--2641},
    bdsk-url-1 = {http://dx.doi.org/10.1109/CVPR.2012.6247983},
    doi = {10.1109/CVPR.2012.6247983},
    }

  • O. Rudovic, V. Pavlovic, and M. Pantic, “Kernel Conditional Ordinal Random Fields for Temporal Segmentation of Facial Action Units,” in Computer Vision – ECCV 2012. Workshops and Demonstrations – Florence, Italy, October 7-13, 2012, Proceedings, Part II, 2012, p. 260–269. doi:10.1007/978-3-642-33868-7_26
    [BibTeX]
    @InProceedings{rudovic12eccvws,
    author = {Ognjen Rudovic and Vladimir Pavlovic and Maja Pantic},
    booktitle = {Computer Vision - {ECCV} 2012. Workshops and Demonstrations - Florence, Italy, October 7-13, 2012, Proceedings, Part {II}},
    title = {Kernel Conditional Ordinal Random Fields for Temporal Segmentation of Facial Action Units},
    year = {2012},
    note = {33\% contribution},
    pages = {260--269},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-642-33868-7_26},
    doi = {10.1007/978-3-642-33868-7_26},
    }

  • S. Shariat and V. Pavlovic, “Improved sequence classification using adaptive segmental sequence alignment,” in Proceedings of the 4th Asian Conference on Machine Learning, ACML 2012, Singapore, Singapore, November 4-6, 2012, 2012, p. 379–394.
    [BibTeX] [Download PDF]
    @inproceedings{shariat12acml,
    Author = {Shahriar Shariat and Vladimir Pavlovic},
    Booktitle = {Proceedings of the 4th Asian Conference on Machine Learning, {ACML} 2012, Singapore, Singapore, November 4-6, 2012},
    Note = {50\% contribution},
    Pages = {379--394},
    Title = {Improved sequence classification using adaptive segmental sequence alignment},
    Url = {http://jmlr.csail.mit.edu/proceedings/papers/v25/shariat12.html},
    Year = {2012},
    Bdsk-Url-1 = {http://jmlr.csail.mit.edu/proceedings/papers/v25/shariat12.html}}

  • W. Yan, X. Han, and V. Pavlovic, “Structured Learning for Multiple Object Tracking,” in British Machine Vision Conference, BMVC 2012, Surrey, UK, September 3-7, 2012, 2012, p. 1–12. doi:10.5244/C.26.48
    [BibTeX]
    @InProceedings{Yan2012BMVC,
    author = {Wang Yan and Xiaoye Han and Vladimir Pavlovic},
    booktitle = {British Machine Vision Conference, {BMVC} 2012, Surrey, UK, September 3-7, 2012},
    title = {Structured Learning for Multiple Object Tracking},
    year = {2012},
    note = {33\% contribution},
    pages = {1--12},
    bdsk-url-1 = {http://dx.doi.org/10.5244/C.26.48},
    doi = {10.5244/C.26.48},
    }

  • S. Yi and V. Pavlovic, “Sparse Granger causality graphs for human action classification,” in Proceedings of the 21st International Conference on Pattern Recognition, ICPR 2012, Tsukuba, Japan, November 11-15, 2012, 2012, p. 3374–3377.
    [BibTeX] [Download PDF]
    @inproceedings{yi12icpr,
    Author = {Saehoon Yi and Vladimir Pavlovic},
    Booktitle = {Proceedings of the 21st International Conference on Pattern Recognition, {ICPR} 2012, Tsukuba, Japan, November 11-15, 2012},
    Note = {50\% contribution},
    Pages = {3374--3377},
    Title = {Sparse Granger causality graphs for human action classification},
    Url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6460888},
    Year = {2012},
    Bdsk-Url-1 = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6460888}}

  • S. Yoon and V. Pavlovic, “Distributed Probabilistic Learning for Camera Networks with Missing Data,” in Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States., 2012, p. 2933–2941.
    [BibTeX] [Download PDF]
    @inproceedings{yoon12nips,
    Author = {Sejong Yoon and Vladimir Pavlovic},
    Booktitle = {Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States.},
    Note = {50\% contribution},
    Pages = {2933--2941},
    Title = {Distributed Probabilistic Learning for Camera Networks with Missing Data},
    Url = {http://papers.nips.cc/paper/4629-distributed-probabilistic-learning-for-camera-networks-with-missing-data},
    Year = {2012},
    Bdsk-Url-1 = {http://papers.nips.cc/paper/4629-distributed-probabilistic-learning-for-camera-networks-with-missing-data}}

  • M. Kim and V. Pavlovic, “Conditional Ordinal Random Fields for Structured Ordinal-Valued Label Prediction,” Data Min. Knowl. Discov., 2012. doi:10.1007/s10618-013-0305-2
    [BibTeX]
    @Article{kim12dmkd:sub,
    author = {Minyoung Kim and Vladimir Pavlovic},
    journal = {Data Min. Knowl. Discov.},
    title = {Conditional Ordinal Random Fields for Structured Ordinal-Valued Label Prediction},
    year = {2012},
    note = {50\% contribution},
    date-added = {2012-12-11 03:35:13 +0000},
    date-modified = {2012-12-11 03:36:29 +0000},
    doi = {10.1007/s10618-013-0305-2},
    }

2011

  • A. Cohen and V. Pavlovic, “An efficient IP approach to constrained multiple face tracking and recognition,” in IEEE International Conference on Computer Vision Workshops, ICCV 2011 Workshops, Barcelona, Spain, November 6-13, 2011, 2011, p. 852–859. doi:10.1109/ICCVW.2011.6130341
    [BibTeX]
    @InProceedings{Cohen2011,
    author = {Andre Cohen and Vladimir Pavlovic},
    booktitle = {{IEEE} International Conference on Computer Vision Workshops, {ICCV} 2011 Workshops, Barcelona, Spain, November 6-13, 2011},
    title = {An efficient {IP} approach to constrained multiple face tracking and recognition},
    year = {2011},
    note = {50\% contribution},
    pages = {852--859},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICCVW.2011.6130341},
    doi = {10.1109/ICCVW.2011.6130341},
    }

  • R. Huang, N. Sang, V. Pavlovic, and D. N. Metaxas, “A Belief Propagation algorithm for bias field estimation and image segmentation,” in 18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, September 11-14, 2011, 2011, p. 37–40. doi:10.1109/ICIP.2011.6116528
    [BibTeX]
    @InProceedings{rui11icip,
    author = {Rui Huang and Nong Sang and Vladimir Pavlovic and Dimitris N. Metaxas},
    booktitle = {18th {IEEE} International Conference on Image Processing, {ICIP} 2011, Brussels, Belgium, September 11-14, 2011},
    title = {A Belief Propagation algorithm for bias field estimation and image segmentation},
    year = {2011},
    note = {25\% contribution},
    pages = {37--40},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICIP.2011.6116528},
    doi = {10.1109/ICIP.2011.6116528},
    }

  • S. Shariat and V. Pavlovic, “Isotonic CCA for sequence alignment and activity recognition,” in IEEE International Conference on Computer Vision, ICCV 2011, Barcelona, Spain, November 6-13, 2011, 2011, p. 2572–2578. doi:10.1109/ICCV.2011.6126545
    [BibTeX]
    @InProceedings{Shariat2011,
    author = {Shahriar Shariat and Vladimir Pavlovic},
    booktitle = {{IEEE} International Conference on Computer Vision, {ICCV} 2011, Barcelona, Spain, November 6-13, 2011},
    title = {Isotonic {CCA} for sequence alignment and activity recognition},
    year = {2011},
    note = {50\% contribution},
    pages = {2572--2578},
    bdsk-url-1 = {http://dx.doi.org/10.1109/ICCV.2011.6126545},
    doi = {10.1109/ICCV.2011.6126545},
    }

  • M. Kim and V. Pavlovic, “Sequence classification via large margin hidden Markov models,” Data Min. Knowl. Discov., vol. 23, iss. 2, p. 322–344, 2011. doi:10.1007/s10618-010-0206-6
    [BibTeX]
    @Article{kim11kdd,
    author = {Minyoung Kim and Vladimir Pavlovic},
    journal = {Data Min. Knowl. Discov.},
    title = {Sequence classification via large margin hidden {Markov} models},
    year = {2011},
    note = {50\% contribution},
    number = {2},
    pages = {322--344},
    volume = {23},
    bdsk-url-1 = {http://dx.doi.org/10.1007/s10618-010-0206-6},
    doi = {10.1007/s10618-010-0206-6},
    }

  • M. Kim and V. Pavlovic, “Central Subspace Dimensionality Reduction Using Covariance Operators,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, iss. 4, p. 657–670, 2011. doi:10.1109/TPAMI.2010.111
    [BibTeX]
    @Article{kim11pami,
    author = {Minyoung Kim and Vladimir Pavlovic},
    journal = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
    title = {Central Subspace Dimensionality Reduction Using Covariance Operators},
    year = {2011},
    note = {50\% contribution},
    number = {4},
    pages = {657--670},
    volume = {33},
    bdsk-url-1 = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.111},
    bdsk-url-2 = {http://dx.doi.org/10.1109/TPAMI.2010.111},
    doi = {10.1109/TPAMI.2010.111},
    }

  • A. Mitrofanova, V. Pavlovic, and B. Mishra, “Prediction of Protein Functions with Gene Ontology and Interspecies Protein Homology Data,” IEEE/ACM Trans. Comput. Biology Bioinform., vol. 8, iss. 3, p. 775–784, 2011. doi:10.1109/TCBB.2010.15
    [BibTeX]
    @Article{mitrofanova11,
    author = {Antonina Mitrofanova and Vladimir Pavlovic and Bud Mishra},
    journal = {{IEEE/ACM} Trans. Comput. Biology Bioinform.},
    title = {Prediction of Protein Functions with Gene Ontology and Interspecies Protein Homology Data},
    year = {2011},
    note = {33\% contribution},
    number = {3},
    pages = {775--784},
    volume = {8},
    bdsk-url-1 = {http://dx.doi.org/10.1109/TCBB.2010.15},
    doi = {10.1109/TCBB.2010.15},
    }

  • T. Parag, V. Pavlovic, and A. Elgammal, “Learning Hypergraph Labeling for Feature Matching,” CoRR, vol. abs/1107.2553, 2011.
    [BibTeX]
    @Article{toufiq11corr,
    author = {Toufiq Parag and Pavlovic, Vladimir and Ahmed Elgammal},
    journal = {CoRR},
    title = {{L}earning {H}ypergraph {L}abeling for {F}eature {M}atching},
    year = {2011},
    note = {33\% contribution},
    volume = {abs/1107.2553},
    bdsk-url-1 = {http://arxiv.org/abs/1107.2553},
    date-added = {2012-12-07 20:04:48 +0000},
    date-modified = {2012-12-07 20:04:48 +0000},
    eprint = {1107.2553},
    eprinttype = {arxiv},
    }

2010

  • A. Cohen and V. Pavlovic, “Reinforcement Learning for Robust and Efficient Real-World Tracking,” in Pattern Recognition (ICPR), 2010 20th International Conference on, 2010, p. 2989–2992. doi:10.1109/ICPR.2010.732
    [BibTeX] [Abstract]

    In this paper we present a new approach for combining several independent trackers into one robust real-time tracker. Unlike previous work that employ multiple tracking objectives used in unison, our tracker manages to determine an optimal sequence of individual trackers given the characteristics present in the video and the desire to achieve maximally efficient tracking. This allows for the selection of fast less-robust trackers when little movement is sensed, while using more robust but computationally intensive trackers in more dynamic scenes. We test this approach on the problem of real-world face tracking. Results show that this approach is a viable method for combining several independent trackers into one robust real-time tracker capable of tracking faces in varied lighting conditions, video resolutions, and with occlusions.

    @conference{cohen2010,
    Abstract = {In this paper we present a new approach for combining several independent trackers into one robust real-time tracker. Unlike previous work that employ multiple tracking objectives used in unison, our tracker manages to determine an optimal sequence of individual trackers given the characteristics present in the video and the desire to achieve maximally efficient tracking. This allows for the selection of fast less-robust trackers when little movement is sensed, while using more robust but computationally intensive trackers in more dynamic scenes. We test this approach on the problem of real-world face tracking. Results show that this approach is a viable method for combining several independent trackers into one robust real-time tracker capable of tracking faces in varied lighting conditions, video resolutions, and with occlusions.},
    Author = {Cohen, Andre and Pavlovic, Vladimir},
    Booktitle = {Pattern Recognition ({ICPR}), 2010 20th International Conference on},
    Date-Added = {2012-12-07 20:04:38 +0000},
    Date-Modified = {2012-12-07 20:04:38 +0000},
    Doi = {10.1109/ICPR.2010.732},
    Isbn = {978-1-4244-7542-1},
    Issn = {1051-4651},
    Note = {50\% contribution},
    Pages = {2989--2992},
    Title = {{R}einforcement {L}earning for {R}obust and {E}fficient {R}eal-{W}orld {T}racking},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICPR.2010.732}}

  • M. Kim and V. Pavlovic, “Structured output ordinal regression for dynamic facial emotion intensity prediction,” in Computer Vision – ECCV 2010, Berlin, Heidelberg, 2010, p. 649–662. doi:10.1007/978-3-642-15558-1_47
    [BibTeX] [Abstract]

    We consider the task of labeling facial emotion intensities in videos, where the emotion intensities to be predicted have ordinal scales (e.g., low, medium, and high) that change in time. A significant challenge is that the rates of increase and decrease differ substantially across subjects. Moreover, the actual absolute differences of intensity values carry little information, with their relative order being more important. To solve the intensity prediction problem we propose a new dynamic ranking model that models the signal intensity at each time as a label on an ordinal scale and links the temporally proximal labels using dynamic smoothness constraints. This new model extends the successful static ordinal regression to a structured (dynamic) setting by using an analogy with Conditional Random Field (CRF) models in structured classification. We show that, although non-convex, the new model can be accurately learned using efficient gradient search. The predictions resulting from this dynamic ranking model show significant improvements over the regular CRFs, which fail to consider ordinal relationships between predicted labels. We also observe substantial improvements over static ranking models that do not exploit temporal dependencies of ordinal predictions. We demonstrate the benefits of our algorithm on the Cohn-Kanade dataset for the dynamic facial emotion intensity prediction problem and illustrate its performance in a controlled synthetic setting.

    @Conference{Kim:2010:SOO:1927006.1927056,
    author = {Kim, Minyoung and Pavlovic, Vladimir},
    booktitle = {Computer Vision - ECCV 2010},
    title = {{S}tructured output ordinal regression for dynamic facial emotion intensity prediction},
    year = {2010},
    address = {Berlin, Heidelberg},
    editor = {Daniilidis, Kostas and Maragos, Petros and Paragios, Nikos},
    note = {50\% contribution},
    pages = {649--662},
    publisher = {Springer-Verlag},
    series = {Lecture Notes in Computer Science},
    volume = {6313},
    abstract = {We consider the task of labeling facial emotion intensities in videos, where the emotion intensities to be predicted have ordinal scales (e.g., low, medium, and high) that change in time. A significant challenge is that the rates of increase and decrease differ substantially across subjects. Moreover, the actual absolute differences of intensity values carry little information, with their relative order being more important. To solve the intensity prediction problem we propose a new dynamic ranking model that models the signal intensity at each time as a label on an ordinal scale and links the temporally proximal labels using dynamic smoothness constraints. This new model extends the successful static ordinal regression to a structured (dynamic) setting by using an analogy with Conditional Random Field (CRF) models in structured classification. We show that, although non-convex, the new model can be accurately learned using efficient gradient search. The predictions resulting from this dynamic ranking model show significant improvements over the regular CRFs, which fail to consider ordinal relationships between predicted labels. We also observe substantial improvements over static ranking models that do not exploit temporal dependencies of ordinal predictions. We demonstrate the benefits of our algorithm on the Cohn-Kanade dataset for the dynamic facial emotion intensity prediction problem and illustrate its performance in a controlled synthetic setting.},
    bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-642-15558-1_47},
    date-added = {2012-12-07 20:04:38 +0000},
    date-modified = {2012-12-07 20:04:38 +0000},
    doi = {10.1007/978-3-642-15558-1_47},
    isbn = {3-642-15557-X, 978-3-642-15557-4},
    }

  • M. Kim and V. Pavlovic, “Hidden Conditional Ordinal Random Fields for Sequence Classification,” in ECML/PKDD, 2010, p. 51–65. doi:10.1007/978-3-642-15883-4_4
    [BibTeX]
    @Conference{kim10ecml,
    author = {Kim, Minyoung and Pavlovic, Vladimir},
    booktitle = {ECML/PKDD},
    title = {{H}idden {C}onditional {O}rdinal {R}andom {F}ields for {S}equence {C}lassification},
    year = {2010},
    note = {50\% contribution},
    pages = {51--65},
    volume = {2},
    date-added = {2012-12-07 20:04:38 +0000},
    date-modified = {2012-12-07 20:04:38 +0000},
    doi = {10.1007/978-3-642-15883-4_4},
    keywords = {ordinal random fields},
    }

  • P. Kuksa, Y. Qi, B. Bai, R. Collobert, J. Weston, V. Pavlovic, and X. Ning, “Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction,” in Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, 2010, p. 128–144. doi:10.1007/978-3-642-15883-4_9
    [BibTeX]
    @conference{kuksa10ecml,
    Address = {Barcelona, Spain},
    Author = {Kuksa, Pavel and Yanjun Qi and Bing Bai and Ronan Collobert and Jason Weston and Pavlovic, Vladimir and Xia Ning},
    Booktitle = {Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010},
    Date-Added = {2012-12-07 20:04:38 +0000},
    Date-Modified = {2012-12-07 20:04:38 +0000},
    Doi = {10.1007/978-3-642-15883-4_9},
    Month = oct,
    Note = {15\% contribution},
    Pages = {128--144},
    Title = {{S}emi-supervised {A}bstraction-{A}ugmented {S}tring {K}ernel for {M}ulti-level {B}io-{R}elation {E}xtraction},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-642-15883-4_9}}

  • P. Kuksa and V. Pavlovic, “Spatial Representation for Efficient Sequence Classification,” in 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, Turkey, 2010, p. 3320–3323. doi:10.1109/ICPR.2010.1159
    [BibTeX]
    @conference{kuksa10icpr,
    Address = {Istanbul, Turkey},
    Author = {Kuksa, Pavel and Pavlovic, Vladimir},
    Booktitle = {20th International Conference on Pattern Recognition, ICPR 2010},
    Date-Added = {2012-12-07 20:04:38 +0000},
    Date-Modified = {2012-12-07 20:04:38 +0000},
    Doi = {10.1109/ICPR.2010.1159},
    Month = aug,
    Note = {50\% contribution},
    Pages = {3320--3323},
    Title = {{S}patial {R}epresentation for {E}fficient {S}equence {C}lassification},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICPR.2010.1159}}

  • S. Shariat, V. Pavlovic, T. Papathomas, A. Braun, and P. Sinha, “Sparse dictionary methods for EEG signal classification in face perception,” in Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on, 2010, p. 331–336. doi:10.1109/MLSP.2010.5589166
    [BibTeX] [Abstract] [Download PDF]

    This paper presents a systematic application of machine learning techniques for classifying high-density EEG signals elicited by face and non-face stimuli. The two stimuli used here are derived from the vase-faces illusion and share the same defining contours, differing only slightly in stimulus space. This emphasizes activity differences related to high-level percepts rather than low-level attributes. This design decision results in a difficult classification task for the ensuing EEG signals. Traditionally, EEG analyses are done on the basis of signal processing techniques involving multiple instance averaging and then a manual examination to detect differentiating components. The present study constitutes an agnostic effort based on purely statistical estimates of three major classifiers: L1-norm logistic regression, group lasso and k Nearest Neighbors (kNN); kNN produced the worst results. L1 regression and group lasso show significantly better performance, while being abl e to identify distinct spatio-temporal signatures. Both L1 regression and group lasso assert the saliency of samples in 170ms, 250ms, 400ms and 600ms after stimulus onset, congruent with the previously reported ERP components associated with face perception. Similarly, spatial locations of salient markers point to the occipital and temporal brain regions, previously implicated in visual object perception. The overall approach presented here can provide a principled way of identifying EEG correlates of other perceptual/cognitive tasks.

    @conference{shahriar2010,
    Abstract = {This paper presents a systematic application of machine learning techniques for classifying high-density EEG signals elicited
    by face and non-face stimuli. The two stimuli used here
    are derived from the vase-faces illusion and share the same
    defining contours, differing only slightly in stimulus space.
    This emphasizes activity differences related to high-level
    percepts rather than low-level attributes. This design decision results in a difficult classification task for the ensuing
    EEG signals. Traditionally, EEG analyses are done on the
    basis of signal processing techniques involving multiple instance averaging and then a manual examination to detect
    differentiating components. The present study constitutes
    an agnostic effort based on purely statistical estimates of
    three major classifiers: L1-norm logistic regression, group
    lasso and k Nearest Neighbors (kNN); kNN produced the
    worst results. L1 regression and group lasso show significantly better performance, while being abl e to identify
    distinct spatio-temporal signatures. Both L1 regression and
    group lasso assert the saliency of samples in 170ms, 250ms,
    400ms and 600ms after stimulus onset, congruent with the
    previously reported ERP components associated with face
    perception. Similarly, spatial locations of salient markers
    point to the occipital and temporal brain regions, previously
    implicated in visual object perception. The overall approach
    presented here can provide a principled way of identifying
    EEG correlates of other perceptual/cognitive tasks.},
    Author = {Shariat, Shahriar and Pavlovic, Vladimir and Thomas Papathomas and Ainsley Braun and Pawan Sinha},
    Booktitle = {Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on},
    Date-Added = {2012-12-07 20:04:38 +0000},
    Date-Modified = {2012-12-07 20:04:38 +0000},
    Doi = {10.1109/MLSP.2010.5589166},
    Issn = {1551-2541},
    Keywords = {EEG signal classification, L1-norm logistic regression},
    Month = {29 2010-sept. 1},
    Note = {20\% contribution},
    Pages = {331--336},
    Title = {{S}parse dictionary methods for {EEG} signal classification in face perception},
    Url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5589166{\&}tag=1},
    Year = {2010},
    Bdsk-Url-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5589166%7B%5C&%7Dtag=1},
    Bdsk-Url-2 = {http://dx.doi.org/10.1109/MLSP.2010.5589166}}

  • A. Makadia, V. Pavlovic, and S. Kumar, “Baselines for Image Annotation,” International Journal of Computer Vision, vol. 90, iss. 1, p. 88–105, 2010. doi:10.1007/s11263-010-0338-6
    [BibTeX]
    @article{makadia10ijcv,
    Author = {Ameesh Makadia and Pavlovic, Vladimir and Sanjiv Kumar},
    Date-Added = {2012-12-07 20:04:38 +0000},
    Date-Modified = {2012-12-07 20:15:43 +0000},
    Doi = {10.1007/s11263-010-0338-6},
    Journal = {International Journal of Computer Vision},
    Note = {33\% contribution},
    Number = {1},
    Pages = {88--105},
    Title = {{B}aselines for {I}mage {A}nnotation},
    Volume = {90},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/s11263-010-0338-6}}

2009

  • M. Kim and V. Pavlovic, “Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings,” in International Conference on Artificial Intelligence and Statistics (AISTATS), Clearwater Beach, FL, 2009.
    [BibTeX]
    @inproceedings{kim09:aistats,
    Address = {Clearwater Beach, FL},
    Author = {Minyoung Kim and Vladimir Pavlovic},
    Booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = apr,
    Note = {40\% acceptance},
    Owner = {vladimir},
    Timestamp = {2009.02.03},
    Title = {Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings},
    Year = {2009},
    Bdsk-File-1 = {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}}

  • P. Kuksa and V. Pavlovic, “Fast Motif Selection for Biological Sequences,” in IEEE Int’l Conf. on Bioinformatics and Biomedicine (BIBM), Washington, DC, 2009. doi:10.1109/bibm.2009.41
    [BibTeX]
    @InProceedings{kuksa09:bibm,
    author = {Pavel Kuksa and Vladimir Pavlovic},
    booktitle = {IEEE Int'l Conf. on Bioinformatics and Biomedicine ({BIBM})},
    title = {Fast Motif Selection for Biological Sequences},
    year = {2009},
    address = {Washington, DC},
    bdsk-file-1 = {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},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/bibm.2009.41},
    owner = {vladimir},
    timestamp = {2010.02.22},
    }

  • P. Kuksa and V. Pavlovic, “Efficient Discovery of Common Patterns in Sequences,” in The Learning Workshop, Clearwater Beach, FL, 2009.
    [BibTeX]
    @inproceedings{kuksa09:snow,
    Address = {Clearwater Beach, FL},
    Author = {Pavel Kuksa and Vladimir Pavlovic},
    Booktitle = {The Learning Workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Owner = {vladimir},
    Timestamp = {2010.02.22},
    Title = {Efficient Discovery of Common Patterns in Sequences},
    Year = {2009}}

  • R. Hunag, V. Pavlovic, and D. N. Metaxas, “Embedded Profile Hidden Markov Models for Shape Analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, 2009.
    [BibTeX]
    @article{huang09:pami,
    Author = {Rui Hunag and Vladimir Pavlovic and Dimitris N. Metaxas},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Journal = TPAMI,
    Owner = {vladimir},
    Timestamp = {2010.02.22},
    Title = {Embedded Profile Hidden Markov Models for Shape Analysis},
    Year = {2009}}

  • M. Kim and V. Pavlovic, “Discriminative Learning for Dynamic State Prediction,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, iss. 10, p. 1847–1861, 2009. doi:10.1109/tpami.2009.37
    [BibTeX]
    @Article{kim09:pami,
    author = {Minyoung Kim and Vladimir Pavlovic},
    journal = TPAMI,
    title = {Discriminative Learning for Dynamic State Prediction},
    year = {2009},
    number = {10},
    pages = {1847--1861},
    volume = {31},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/tpami.2009.37},
    owner = {vladimir},
    timestamp = {2009.02.03},
    }

  • M. Kim and V. Pavlovic, “Fast Multiple Kernel Learning via Large Margin Parzen Window Estimation,” Pattern Recognition, 2009.
    [BibTeX]
    @article{kim09:pr,
    Author = {Minyoung Kim and Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2019-09-09 16:39:37 -0400},
    Journal = {Pattern Recognition},
    Note = {Under review},
    Owner = {vladimir},
    Timestamp = {2010.02.22},
    Title = {Fast Multiple Kernel Learning via Large Margin Parzen Window Estimation},
    Year = {2009}}

  • P. P. Kuksa, P. Huang, and V. Pavlovic, “Efficient use of unlabeled data for protein sequence classification: a comparative study,” BMC Bioinformatics, vol. 10, iss. S-14, 2009. doi:10.1186/1471-2105-10-s4-s2
    [BibTeX]
    @Article{kuksa09:bmc,
    author = {Pavel P. Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    journal = {BMC Bioinformatics},
    title = {Efficient use of unlabeled data for protein sequence classification: a comparative study},
    year = {2009},
    number = {S-14},
    volume = {10},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1186/1471-2105-10-s4-s2},
    owner = {vladimir},
    timestamp = {2010.02.22},
    }

  • P. Kuksa and V. Pavlovic, “Efficient alignment-free DNA barcode analytics,” BMC Bioinformatics, vol. 10, iss. S-14, 2009. doi:10.1186/1471-2105-10-s14-s9
    [BibTeX]
    @Article{kuksa09:bmc2,
    author = {Pavel Kuksa and Vladimir Pavlovic},
    journal = {BMC Bioinformatics},
    title = {Efficient alignment-free DNA barcode analytics},
    year = {2009},
    number = {S-14},
    volume = {10},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1186/1471-2105-10-s14-s9},
    owner = {vladimir},
    timestamp = {2010.02.22},
    }

2008

  • P. Kuksa, P. Huang, and V. Pavlovic, Spatially-constrained sample kernel for sequence classification, 2008.
    [BibTeX]
    @misc{kuksa08snow,
    Author = {Pavel Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Howpublished = {Snowbird Learning Workshop, Utah},
    Month = apr,
    Owner = {vladimir},
    Timestamp = {2008.09.08},
    Title = {Spatially-constrained sample kernel for sequence classification},
    Year = {2008}}

  • M. Kim and V. Pavlovic, “Dimensionality Reduction using Covariance Operator Inverse Regression,” in IEEE Conf. Computer Vision and Pattern Recognition, Anchorage, AK, 2008. doi:10.1109/cvpr.2008.4587404
    [BibTeX] [Download PDF]
    @InProceedings{kim08cvpr_coir,
    author = {Minyoung Kim and Vladimir Pavlovic},
    booktitle = CVPR,
    title = {Dimensionality Reduction using Covariance Operator Inverse Regression},
    year = {2008},
    address = {Anchorage, AK},
    month = jun,
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/learning/regression/coir/coir.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/cvpr.2008.4587404},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kim08cvpr_coir.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/learning/regression/coir/coir.html},
    }

  • M. Kim, S. Kumar, V. Pavlovic, and H. Rowley, “Face Tracking and Recognition with Visual Constraints in Real-World Videos,” in IEEE Conf. Computer Vision and Pattern Recognition, Anchorage, AK, 2008. doi:10.1109/cvpr.2008.4587572
    [BibTeX] [Download PDF]
    @InProceedings{kim08cvpr_face,
    author = {Minyoung Kim and Sanjiv Kumar and Vladimir Pavlovic and Henry Rowley},
    booktitle = CVPR,
    title = {Face Tracking and Recognition with Visual Constraints in Real-World Videos},
    year = {2008},
    address = {Anchorage, AK},
    month = jun,
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/motion/face/face.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/cvpr.2008.4587572},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kim08cvpr_face.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/motion/face/face.html},
    }

  • P. Kuksa, P. Huang, and V. Pavlovic, “A fast, semi-supervised learning method for protein sequence classification,” in 8th International Workshop on Data Mining in Bioinformatics (BIOKDD 2008), Las Vegas, NV, 2008, p. 29–37.
    [BibTeX] [Download PDF]
    @InProceedings{kuksa008biokdd,
    author = {Pavel Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    booktitle = {8th International Workshop on Data Mining in Bioinformatics (BIOKDD 2008)},
    title = {A fast, semi-supervised learning method for protein sequence classification},
    year = {2008},
    address = {Las Vegas, NV},
    month = aug,
    note = {Acceptance 30\% (8/25)},
    pages = {29--37},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kuksa08biokdd.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    }

  • P. Kuksa and V. Pavlovic, “Approximate Substructure Matching for Biological Sequence Classification,” in Machine Learning in Computational Biology Workshop, 2008.
    [BibTeX]
    @inproceedings{kuksa08:mlcb,
    Author = {Pavel Kuksa and Vladimir Pavlovic},
    Booktitle = {Machine Learning in Computational Biology Workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = dec,
    Owner = {vladimir},
    Timestamp = {2009.02.03},
    Title = {Approximate Substructure Matching for Biological Sequence Classification},
    Year = {2008}}

  • P. Kuksa, P. Huang, and V. Pavlovic, “On the role of local matching for efficient semi-supervised protein sequence classification,” in IEEE Int’l Conf. Bioinformatics and Biomedicine (BIBM), Philadelphia, PA, 2008. doi:10.1109/bibm.2008.52
    [BibTeX] [Download PDF]
    @InProceedings{kuksa08bibm,
    author = {Pavel Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    booktitle = {IEEE Int'l Conf. Bioinformatics and Biomedicine ({BIBM})},
    title = {On the role of local matching for efficient semi-supervised protein sequence classification},
    year = {2008},
    address = {Philadelphia, PA},
    month = nov,
    note = {Acceptance 24\% (38/156)},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/bibm.2008.52},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kuksa08bibm.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    }

  • P. Kuksa, P. Huang, and V. Pavlovic, “Fast and Accurate Multi-class Protein Fold Recognition with Spatial Sample Kernels,” in Computational Systems Bioinformatics: Proceedings of the CSB2008 Conference, Stanford, CA, 2008, p. 133–143. doi:10.1142/9781848162648_0012
    [BibTeX] [Download PDF]
    @InProceedings{kuksa08csb,
    author = {Pavel Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    booktitle = {Computational Systems Bioinformatics: Proceedings of the CSB2008 Conference},
    title = {Fast and Accurate Multi-class Protein Fold Recognition with Spatial Sample Kernels},
    year = {2008},
    address = {Stanford, CA},
    month = aug,
    note = {Acceptance 22\% (30/135)},
    pages = {133--143},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1142/9781848162648_0012},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kuksa08csb.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    }

  • P. Kuksa, P. Huang, and V. Pavlovic, “Fast Protein Homology and Fold Detection with Sparse Spatial Sample Kernels,” in Int’l Conf. Pattern Recognition, Tampa, FL, 2008. doi:10.1109/icpr.2008.4761450
    [BibTeX] [Download PDF]
    @InProceedings{kuksa08icpr,
    author = {Pavel Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    booktitle = {Int'l Conf. Pattern Recognition},
    title = {Fast Protein Homology and Fold Detection with Sparse Spatial Sample Kernels},
    year = {2008},
    address = {Tampa, FL},
    month = dec,
    note = {Acceptance 15\%},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/icpr.2008.4761450},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kuksa08icpr.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    }

  • P. Kuksa, P. Huang, and V. Pavlovic, “Scalable Algorithms for String Kernels with Inexact Matching,” in Neural Information Processing Systems (NIPS), Vancouver, Canada, 2008.
    [BibTeX] [Download PDF]
    @InProceedings{kuksa08nips,
    author = {Pavel Kuksa and Pai-Hsi Huang and Vladimir Pavlovic},
    booktitle = {Neural Information Processing Systems (NIPS)},
    title = {Scalable Algorithms for String Kernels with Inexact Matching},
    year = {2008},
    address = {Vancouver, Canada},
    month = dec,
    note = {Acceptance 12\% (123/1022)},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kuksa08nips.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/bioinfo/spatial-kernels/spatial-kernels.html},
    }

  • A. Makadia, V. Pavlovic, and S. Kumar, “A New Baseline for Image Annotation,” in European Conf. Computer Vision, Marseille, France, 2008. doi:10.1007/978-3-540-88690-7_24
    [BibTeX] [Download PDF]
    @InProceedings{makadia08eccv,
    author = {Ameesh Makadia and Vladimir Pavlovic and Sanjiv Kumar},
    booktitle = {European Conf. Computer Vision},
    title = {A New Baseline for Image Annotation},
    year = {2008},
    address = {Marseille, France},
    month = oct,
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/projects.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1007/978-3-540-88690-7_24},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/makadia08eccv.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/projects.html},
    }

  • A. Mitrofanova, V. Pavlovic, and B. Mishra, “Integrative Protein Function Transfer using Factor Graphs and Heterogeneous Data Sources,” in IEEE Int’l Conf. Bioinformatics and Biomedicine (BIBM), Philadelphia, PA, 2008. doi:10.1109/bibm.2008.65
    [BibTeX] [Download PDF]
    @InProceedings{mitrofanova08bibm,
    author = {Antonina Mitrofanova and Vladimir Pavlovic and Bud Mishra},
    booktitle = {IEEE Int'l Conf. Bioinformatics and Biomedicine ({BIBM})},
    title = {Integrative Protein Function Transfer using Factor Graphs and Heterogeneous Data Sources},
    year = {2008},
    address = {Philadelphia, PA},
    month = nov,
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/bioinfo.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/bibm.2008.65},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/mitrofanova08bibm.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/bioinfo/bioinfo.html},
    }

  • K. Moon and V. Pavlovic, “Monocular 3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis,” in Fifth Canadian Conference on Computer and Robot Vision, Windsor, ON, 2008.
    [BibTeX] [Download PDF]
    @InProceedings{moon08crv,
    author = {Kooksang Moon and Vladimir Pavlovic},
    booktitle = {Fifth Canadian Conference on Computer and Robot Vision},
    title = {Monocular 3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis},
    year = {2008},
    address = {Windsor, ON},
    month = may,
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/motion/motion.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/moon08crv.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.08},
    url = {http://seqam.rutgers.edu/projects/motion/motion.html},
    }

  • K. Moon and V. Pavlovic, “Visual inference using Gaussian process manifold kernel dimensionality reduction,” in IEEE Int’l Workshop Machine Learning in Signal Processing, Cancun, Mexico: , 2008.
    [BibTeX] [Download PDF]
    @InCollection{moon08mlsp,
    author = {Kooksang Moon and Vladimir Pavlovic},
    booktitle = {IEEE Int'l Workshop Machine Learning in Signal Processing},
    title = {Visual inference using Gaussian process manifold kernel dimensionality reduction},
    year = {2008},
    address = {Cancun, Mexico},
    month = oct,
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/learning/regression/gpmkdr/gpmkdr.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/moon08mlsp.pdf:PDF},
    owner = {vladimir},
    timestamp = {2008.09.11},
    url = {http://seqam.rutgers.edu/projects/learning/regression/gpmkdr/gpmkdr.html},
    }

  • R. Huang, V. Pavlovic, and D. Metaxas, “A new spatio-temporal MRF framework for video-based object segmentation,” in 1st International Workshop on Machine Learning for Vision-based Motion Analysis (MLVMA’08), in conjunction wih ECCV 2008, Marseille, France: , 2008.
    [BibTeX] [Download PDF]
    @incollection{rhuang08mlvma,
    Address = {Marseille, France},
    Author = {Rui Huang and Vladimir Pavlovic and Dimitris Metaxas},
    Booktitle = {1st International Workshop on Machine Learning for Vision-based Motion Analysis (MLVMA'08), in conjunction wih ECCV 2008},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = oct,
    Owner = {vladimir},
    Timestamp = {2008.09.11},
    Title = {A new spatio-temporal MRF framework for video-based object segmentation},
    Url = {http://seqam.rutgers.edu/projects/shape/shape.html},
    Year = {2008},
    Bdsk-Url-1 = {http://seqam.rutgers.edu/projects/shape/shape.html}}

  • Y. Jing, V. Pavlovic, and J. M. Rehg, “Boosted Bayesian network classifiers,” Machine Learning Journal, vol. 73, iss. 2, 2008. doi:10.1007/s10994-008-5065-7
    [BibTeX] [Download PDF]
    @Article{jing08:mlj,
    author = {Y. Jing and V. Pavlovic and J. M. Rehg},
    journal = {Machine Learning Journal},
    title = {Boosted {Bayesian} network classifiers},
    year = {2008},
    month = nov,
    note = {33\% contribution},
    number = {2},
    volume = {73},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/learning/bbn/bbn.html},
    bdsk-url-2 = {http://dx.doi.org/10.1007/s10994-008-5065-7},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1007/s10994-008-5065-7},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/jing08mlj.pdf:PDF},
    url = {http://seqam.rutgers.edu/projects/learning/bbn/bbn.html},
    }

  • P. Huang and V. Pavlovic, “Protein homology detection with biologically inspired features and interpretable statistical models,” Int. J. Data Min. Bioinformatics, vol. 2, iss. 2, p. 157–175, 2008. doi:10.1504/IJDMB.2008.019096
    [BibTeX] [Download PDF]
    @Article{phuang08:ijdmb,
    author = {Pai-Hsi Huang and Vladimir Pavlovic},
    journal = {Int. J. Data Min. Bioinformatics},
    title = {Protein homology detection with biologically inspired features and interpretable statistical models},
    year = {2008},
    issn = {1748-5673},
    note = {50\% contribution},
    number = {2},
    pages = {157--175},
    volume = {2},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/protein/protein.html},
    bdsk-url-2 = {http://dx.doi.org/10.1504/IJDMB.2008.019096},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1504/IJDMB.2008.019096},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/phuang07ijdmb.pdf:PDF},
    url = {http://seqam.rutgers.edu/projects/bioinfo/protein/protein.html},
    }

2007

  • M. Kim, S. Kumar, V. Pavlovic, and H. Rowley, “Face Tracking and Recognition with Visual Constrains,” Rutgers University, Dept. of Computer Science, DCS-TR-623, 2007.
    [BibTeX]
    @TechReport{kim07:googtr,
    author = {Minyoung Kim and Sanjiv Kumar and Vladimir Pavlovic and Henry Rowley},
    institution = {Rutgers University, Dept. of Computer Science},
    title = {Face Tracking and Recognition with Visual Constrains},
    year = {2007},
    month = dec,
    number = {DCS-TR-623},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {kim07googtr.pdf:http\:/www.cs.rutgers.edu/~vladimir/pub/kim07googtr.pdf:PDF},
    owner = {vladimir},
    timestamp = {2007.12.20},
    }

  • M. Kim and V. Pavlovic, “Covariance Kernels and Dimensionality Reduction for Regression,” Rutgers University, Dept. of Computer Science, DCS-TR-622, 2007.
    [BibTeX]
    @TechReport{kim07:tr,
    author = {Minyoung Kim and Vladimir Pavlovic},
    institution = {Rutgers University, Dept. of Computer Science},
    title = {Covariance Kernels and Dimensionality Reduction for Regression},
    year = {2007},
    month = dec,
    number = {DCS-TR-622},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {kim07tr.pdf:http\:/www.cs.rutgers.edu/~vladimir/pub/kim07tr.pdf:PDF},
    owner = {vladimir},
    timestamp = {2007.12.20},
    }

  • K. Moon and V. Pavlovic, “Gaussian Process Manifold Kernel Dimensionality Reduction,” Rutgers University, Dept. of Computer Science, DCS-TR-621, 2007.
    [BibTeX]
    @TechReport{moon07:tr,
    author = {Kooksang Moon and Vladimir Pavlovic},
    institution = {Rutgers University, Dept. of Computer Science},
    title = {Gaussian Process Manifold Kernel Dimensionality Reduction},
    year = {2007},
    month = dec,
    number = {DCS-TR-621},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {moon07tr.pdf:http\:/www.cs.rutgers.edu/~vladimir/pub/moon07tr.pdf:PDF},
    owner = {vladimir},
    timestamp = {2007.12.20},
    }

  • P. Kuksa and V. Pavlovic, Kernel methods for DNA barcoding, 2007.
    [BibTeX]
    @misc{kuksa07snow,
    Author = {Pavel Kuksa and Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Howpublished = {Snowbird Learning Workshop, San Juan, Puerto Rico},
    Month = mar,
    Owner = {vladimir},
    Timestamp = {2008.09.08},
    Title = {Kernel methods for {DNA} barcoding},
    Year = {2007}}

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “Embedded Profile Hidden Markov Models for Shape Analysis,” in IEEE Int’l Conf. Computer Vision, Rio De Janeiro, Brazil, 2007. doi:10.1109/iccv.2007.4409026
    [BibTeX] [Download PDF]
    @InProceedings{huang07:iccv,
    author = {Rui Huang and Vladimir Pavlovic and Dimitris N. Metaxas},
    booktitle = ICCV,
    title = {Embedded Profile Hidden {Markov} Models for Shape Analysis},
    year = {2007},
    address = {Rio De Janeiro, Brazil},
    month = oct,
    note = {8 pages, 33\% contribution, 24.5\% acceptance rate.},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/shape/shape_ephmm/shape_ephmm.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/iccv.2007.4409026},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/huang07iccv.pdf:PDF},
    owner = {vladimir},
    timestamp = {2007.08.28},
    url = {http://seqam.rutgers.edu/projects/shape/shape_ephmm/shape_ephmm.html},
    }

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “Shape analysis using curvature-based descriptors and profile hidden Markov models,” in IEEE Int’l Symposium on Biomedical Imaging (ISBI), 2007, p. 1220–1223. doi:10.1109/isbi.2007.357078
    [BibTeX] [Download PDF]
    @InProceedings{huang07:isbi,
    author = {R. Huang and V. Pavlovic and D. N. Metaxas},
    booktitle = {IEEE Int'l Symposium on Biomedical Imaging (ISBI)},
    title = {Shape analysis using curvature-based descriptors and profile hidden {Markov} models},
    year = {2007},
    month = apr,
    note = {33\% contribution. Poster. N/A acceptance rate},
    pages = {1220--1223},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/shape/shape_ephmm/shape_ephmm.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/isbi.2007.357078},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/huang07isbi.pdf:PDF},
    url = {http://seqam.rutgers.edu/projects/shape/shape_ephmm/shape_ephmm.html},
    }

  • M. Kim and V. Pavlovic, “Discriminative Learning of Dynamical Systems for Motion Tracking,” in IEEE Conf. Computer Vision and Pattern Recognition, 2007. doi:10.1109/cvpr.2007.383242
    [BibTeX] [Download PDF]
    @InProceedings{kim07:cvpr,
    author = {M. Kim and V. Pavlovic},
    booktitle = CVPR,
    title = {Discriminative Learning of Dynamical Systems for Motion Tracking},
    year = {2007},
    note = {50\% contribution. Poster, 28.2\% acceptance rate},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/motion/ddm/index.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/cvpr.2007.383242},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kim07cvpr.pdf:PDF},
    url = {http://seqam.rutgers.edu/projects/motion/ddm/index.html},
    }

  • M. Kim and V. Pavlovic, “Conditional State Space Models for Discriminative Motion Estimation,” in IEEE Int’l Conf. Computer Vision, Rio De Janeiro, Brazil, 2007. doi:10.1109/iccv.2007.4408943
    [BibTeX] [Download PDF]
    @InProceedings{kim07:iccv,
    author = {Minyoung Kim and Vladimir Pavlovic},
    booktitle = ICCV,
    title = {Conditional State Space Models for Discriminative Motion Estimation},
    year = {2007},
    address = {Rio De Janeiro, Brazil},
    month = oct,
    note = {8 pages, 50\% contribution, 24.5\% acceptance rate.},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/motion/ddm/index.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/iccv.2007.4408943},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kim07iccv.pdf:PDF},
    owner = {vladimir},
    timestamp = {2007.08.28},
    url = {http://seqam.rutgers.edu/projects/motion/ddm/index.html},
    }

  • M. Kim and V. Pavlovic, “A Recursive Method for Discriminative Mixture Learning,” in Int’l Conf. Machine Learning (ICML), Corvallis, OR, 2007. doi:10.1145/1273496.1273548
    [BibTeX] [Download PDF]
    @InProceedings{kim07:icml,
    author = {M. Kim and V. Pavlovic},
    booktitle = {Int'l Conf. Machine Learning (ICML)},
    title = {A Recursive Method for Discriminative Mixture Learning},
    year = {2007},
    address = {Corvallis, OR},
    month = jun,
    note = {50\% contribution. Oral presentation, 29\% acceptance rate},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/motion/seqgroup/seqgroup.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1145/1273496.1273548},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kim07icml.pdf:PDF},
    url = {http://seqam.rutgers.edu/projects/motion/seqgroup/seqgroup.html},
    }

  • P. Kuksa and V. Pavlovic, “Fast barcode-based species identification using string kernels,” in 2nd International Barcode of Life Conference, Taipei, Taiwan, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{kuksa07:bol,
    Address = {Taipei, Taiwan},
    Author = {Pavel Kuksa and Vladimir Pavlovic},
    Booktitle = {2nd International Barcode of Life Conference},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = sep,
    Note = {1 page, 50\% contribution, N/A acceptance rate.},
    Owner = {vladimir},
    Timestamp = {2007.08.28},
    Title = {Fast barcode-based species identification using string kernels},
    Url = {http://seqam.rutgers.edu/projects/bioinfo/barcoding/barcoding.html},
    Year = {2007},
    Bdsk-Url-1 = {http://seqam.rutgers.edu/projects/bioinfo/barcoding/barcoding.html}}

  • P. Kuksa and V. Pavlovic, “Fast kernel methods for SVM sequence classifiers,” in The Workshop on Algorithms in Bioinformatics (WABI), Philadelphia, PA, 2007.
    [BibTeX] [Download PDF]
    @InProceedings{kuksa07:wabi,
    author = {P. Kuksa and V. Pavlovic},
    booktitle = {The Workshop on Algorithms in Bioinformatics (WABI)},
    title = {Fast kernel methods for SVM sequence classifiers},
    year = {2007},
    address = {Philadelphia, PA},
    month = sep,
    note = {50\% contribution. Oral presentation, 28\% acceptance rate},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/bioinfo/barcoding/barcoding.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/kuksa07wabi.pdf:PDF},
    rating = {4},
    url = {http://seqam.rutgers.edu/projects/bioinfo/barcoding/barcoding.html},
    }

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A Graphical Model Framework for Image Segmentation,” in Applied Graph Theory in Computer Vision and Pattern Recognition, A. Kandel, H. Bunke, and M. Last, Eds., Springer, 2007, vol. 52, p. 43–64.
    [BibTeX] [Download PDF]
    @InCollection{huang07:agt,
    author = {Rui Huang and Vladimir Pavlovic and Dimitris N. Metaxas},
    booktitle = {Applied Graph Theory in Computer Vision and Pattern Recognition},
    publisher = {Springer},
    title = {A Graphical Model Framework for Image Segmentation},
    year = {2007},
    chapter = {2},
    editor = {Kandel, Abraham and Bunke, Horst and Last, Mark},
    pages = {43--64},
    series = {Studies in Computational Intelligence},
    volume = {52},
    bdsk-url-1 = {http://seqam.rutgers.edu/projects/shape/segmentation/segmentation.html},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    file = {:http\:/www.cs.rutgers.edu/~vladimir/pub/huang07agt.pdf:PDF},
    url = {http://seqam.rutgers.edu/projects/shape/segmentation/segmentation.html},
    }

  • K. Moon and V. Pavlovic, “Graphical Models for Human Motion Modeling,” in Human Motion – Understanding, Modeling, Capture and Animation, K. R. D. Metaxas and B. Rosenhahn, Eds., Springer, 2007. doi:10.1007/978-1-4020-6693-1_7
    [BibTeX] [Download PDF]
    @InCollection{moon07:hm,
    author = {K. Moon and V. Pavlovic},
    booktitle = {Human Motion - Understanding, Modeling, Capture and Animation},
    publisher = {Springer},
    title = {Graphical Models for Human Motion Modeling},
    year = {2007},
    editor = {D. Metaxas, R. Klette and B. Rosenhahn},
    note = {50\% contribution},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/moon07hm.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1007/978-1-4020-6693-1_7},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/moon07hm.pdf},
    }

2006

  • M. Kim and V. Pavlovic, “Discriminative Tracking Methods,” Rutgers University, DCS-TR6xx, 2006.
    [BibTeX] [Download PDF]
    @techreport{kim06:dttr,
    Author = {Minyoung Kim and Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Institution = {Rutgers University},
    Number = {DCS-TR6xx},
    Title = {Discriminative Tracking Methods},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/kim06dttr.pdf},
    Year = {2006},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/kim06dttr.pdf}}

  • P. Kuksa and V. Pavlovic, “Kernel methods for DNA barcoding,” Rutgers University, DCS-TR606, 2006.
    [BibTeX] [Download PDF]
    @techreport{kuksa06:tr,
    Author = {Pavel Kuksa and Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Institution = {Rutgers University},
    Number = {DCS-TR606},
    Title = {Kernel methods for DNA barcoding},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/kuksa06tr.pdf},
    Year = {2006},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/kuksa06tr.pdf}}

  • K. Moon and V. Pavlovic, “Monocular 3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis,” Rutgers University, DCS-TR6xx, 2006.
    [BibTeX] [Download PDF]
    @techreport{moon06:plsatr,
    Author = {Kooksang Moon and Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Institution = {Rutgers University},
    Number = {DCS-TR6xx},
    Title = {Monocular 3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/moon06plsatr.pdf},
    Year = {2006},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/moon06plsatr.pdf}}

  • R. Huang and V. Pavlovic, “Embedded profile hidden Markov models for shape analysis,” Rutgers University, DCS-TR6xx, 2006. doi:10.1109/iccv.2007.4409026
    [BibTeX] [Download PDF]
    @TechReport{rhuang06:ephmmtr,
    author = {Rui Huang and Vladimir Pavlovic},
    institution = {Rutgers University},
    title = {Embedded profile hidden {Markov} models for shape analysis},
    year = {2006},
    number = {DCS-TR6xx},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/rhuang06ephmmtr.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/iccv.2007.4409026},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/rhuang06ephmmtr.pdf},
    }

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape,” in IEEE Int’l Conf. Image Processing, Atlanta, GA, 2006, p. 2121–4. doi:10.1109/icip.2006.312827
    [BibTeX] [Download PDF]
    @InProceedings{huang06:icip,
    author = {R. Huang and V. Pavlovic and D. N. Metaxas},
    booktitle = ICIP,
    title = {A Profile Hidden {Markov} Model Framework for Modeling and Analysis of Shape},
    year = {2006},
    address = {Atlanta, GA},
    month = oct,
    note = {33\% contribution. Poster. 46\% acceptance rate},
    pages = {2121--4},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/huang07icip.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/icip.2006.312827},
    keywords = {profile hmm, shape modeling},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/huang07icip.pdf},
    }

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A tightly coupled region-shape framework for 3D medical image segmentation,” in Int’l Symposium Biomedical Imaging, 2006.
    [BibTeX] [Download PDF]
    @inproceedings{huang06:isbi,
    Author = {Rui Huang and Vladimir Pavlovic and Dimitris N. Metaxas},
    Booktitle = {Int'l Symposium Biomedical Imaging},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {33\% contribution. Poster. 60\% acceptance rate},
    Title = {A tightly coupled region-shape framework for {3D} medical image segmentation},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/huang06isbi.pdf},
    Year = {2006},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/huang06isbi.pdf}}

  • M. Kim and V. Pavlovic, “Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification,” in IEEE Conf. Computer Vision and Pattern Recognition, New York, NY, 2006, p. 268–275.
    [BibTeX] [Download PDF]
    @inproceedings{kim06:cvpr,
    Address = {New York, NY},
    Author = {M. Kim and V. Pavlovic},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Keywords = {motion classification, discriminative generative models},
    Month = jun,
    Note = {50\% contribution. Poster, 23.3\% acceptance rate},
    Pages = {268--275},
    Title = {Discriminative Learning of Mixture of {Bayesian} Network Classifiers for Sequence Classification},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/kim06cvpr.pdf},
    Year = {2006},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/kim06cvpr.pdf}}

  • K. Moon and V. Pavlovic, “Impact of Dynamics on Subspace Embedding and Tracking of Sequences,” in IEEE Conf. Computer Vision and Pattern Recognition, 2006, p. 198–205.
    [BibTeX] [Download PDF]
    @inproceedings{moon06:cvpr,
    Author = {K. Moon and V. Pavlovic},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Keywords = {tracking, subspace, dynamics modeling},
    Note = {50\% contribution. Poster, 23.3\% acceptance rate},
    Pages = {198--205},
    Title = {Impact of Dynamics on Subspace Embedding and Tracking of Sequences},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/moon05cvpr.pdf},
    Year = {2006},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/moon05cvpr.pdf}}

  • P-H. Huang and V. Pavlovic, “Sparse Logistic Classifiers for Interpretable Protein Homology Detection,” in International Workshop on Datamining in Bioinformatics, IEEE Int’l Conf. Datamining (ICDM), Hong Kong, 2006, p. 99–103. doi:10.1109/icdmw.2006.152
    [BibTeX] [Download PDF]
    @InProceedings{phuang06:icdm,
    author = {P-H. Huang and V. Pavlovic},
    booktitle = {International Workshop on Datamining in Bioinformatics, IEEE Int'l Conf. Datamining (ICDM)},
    title = {Sparse Logistic Classifiers for Interpretable Protein Homology Detection},
    year = {2006},
    address = {Hong Kong},
    month = dec,
    note = {50\% contribution. Oral presentation, 21.2\% acceptance rate},
    pages = {99--103},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/phuang06icdm.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/icdmw.2006.152},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/phuang06icdm.pdf},
    }

  • S. Carroll and V. Pavlovic, “Protein Classification Using Probabilistic Chain Graphs and the Gene Ontology Structure,” Bioinformatics, vol. 22, iss. 15, p. 1871–8, 2006. doi:10.1093/bioinformatics/btl187
    [BibTeX] [Download PDF]
    @Article{carroll06:bioinf,
    author = {S. Carroll and V. Pavlovic},
    journal = BIO,
    title = {Protein Classification Using Probabilistic Chain Graphs and the Gene Ontology Structure},
    year = {2006},
    month = aug,
    note = {50\% contribution},
    number = {15},
    pages = {1871--8},
    volume = {22},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/carroll06bi.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/bioinformatics/btl187},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/carroll06bi.pdf},
    }

2005

  • S. Carroll and V. Pavlovic, “Protein Classification Using Probabilistic Chain Graphs and the Gene Ontology Structure,” Dept. of Computer Science, Rutgers University, RU-DCS-TR587, 2005. doi:10.1093/bioinformatics/btl187
    [BibTeX] [Download PDF]
    @TechReport{carroll05:tr,
    author = {S. Carroll and V. Pavlovic},
    institution = {Dept. of Computer Science, Rutgers University},
    title = {Protein Classification Using Probabilistic Chain Graphs and the Gene Ontology Structure},
    year = {2005},
    number = {RU-DCS-TR587},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/carroll05tr.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/bioinformatics/btl187},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/carroll05tr.pdf},
    }

  • Y. Jing, V. Pavlovic, and J. M. Rehg, “Boosted Bayesian Network Classifiers,” College of Computing, Georgia Institute of Technology, GIT-GVU-05-23, 2005. doi:10.1007/s10994-008-5065-7
    [BibTeX] [Download PDF]
    @TechReport{jing05:tr,
    author = {Y. Jing and V. Pavlovic and J.M. Rehg},
    institution = {College of Computing, Georgia Institute of Technology},
    title = {Boosted {Bayesian} Network Classifiers},
    year = {2005},
    number = {GIT-GVU-05-23},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/jing05tr.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1007/s10994-008-5065-7},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/jing05tr.pdf},
    }

  • M. Kim and V. Pavlovic, “Discriminative Learning of Mixture of Bayesian Network Classifiers for Sequence Classification,” Dept. of Computer Science, Rutgers University, RU-DCS-TR588, 2005.
    [BibTeX] [Download PDF]
    @techreport{kim05:tr,
    Author = {M. Kim and V. Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Institution = {Dept. of Computer Science, Rutgers University},
    Number = {RU-DCS-TR588},
    Title = {Discriminative Learning of Mixture of {Bayesian} Network Classifiers for Sequence Classification},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/kim05tr.pdf},
    Year = {2005},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/kim05tr.pdf}}

  • K. Moon and V. Pavlovic, “Impact of Dynamics on Subspace Embedding and Tracking of Sequences,” Dept. of Computer Science, Rutgers University, RU-DCS-TR589, 2005.
    [BibTeX] [Download PDF]
    @techreport{moon05:tr,
    Author = {K. Moon and V. Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Institution = {Dept. of Computer Science, Rutgers University},
    Number = {RU-DCS-TR589},
    Title = {Impact of Dynamics on Subspace Embedding and Tracking of Sequences},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/moon05tr.pdf},
    Year = {2005},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/moon05tr.pdf}}

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous Constraints,” in Computer Vision for Biomedical Image Application: Current Techniques and Future Trends, Beijing, PRC, 2005. doi:10.1007/11569541_10
    [BibTeX] [Download PDF]
    @InProceedings{huang05:iccv,
    author = {R. Huang and V. Pavlovic and D. N. Metaxas},
    booktitle = {Computer Vision for Biomedical Image Application: Current Techniques and Future Trends},
    title = {A Hybrid Framework for Image Segmentation Using Probabilistic Integration of Heterogeneous Constraints},
    year = {2005},
    address = {Beijing, PRC},
    month = oct,
    note = {33\% contribution. Poster. N/A acceptance rate},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/huang05iccv.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1007/11569541_10},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/huang05iccv.pdf},
    }

  • Y. Jing, V. Pavlovic, and J. M. Rehg, “Efficient discriminative learning of Bayesian network classifier via Boosted Augmented Naive Bayes,” in International Conf. Machine Learning, Bonn, Germany, 2005. doi:10.1145/1102351.1102398
    [BibTeX] [Download PDF]
    @InProceedings{jing05:icml,
    author = {Y. Jing and V. Pavlovic and J.M. Rehg},
    booktitle = {International Conf. Machine Learning},
    title = {Efficient discriminative learning of {Bayesian} network classifier via Boosted Augmented Naive Bayes},
    year = {2005},
    address = {Bonn, Germany},
    month = aug,
    note = {{\bf Distinguished student paper award}. 33\% contribution. Oral presentation, 27.3\% acceptance rate},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/jing05icml.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1145/1102351.1102398},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/jing05icml.pdf},
    }

  • K. Moon and V. Pavlovic, “Robust tracking of articulated layers,” in Vision for HCI Workshop, San Diego, CA, 2005.
    [BibTeX] [Download PDF]
    @inproceedings{moon05:cvpr,
    Address = {San Diego, CA},
    Author = {K. Moon and V. Pavlovic},
    Booktitle = {Vision for HCI Workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jun,
    Note = {50\% contribution. Oral presentation, 23\% acceptance rate},
    Title = {Robust tracking of articulated layers},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/moon05cvpr.pdf},
    Year = {2005},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/moon05cvpr.pdf}}

  • P-H. Huang and V. Pavlovic, “Protein homology detection using sparse profile hidden Markov models,” in Int’l Conf. Intelligent Systems for Molecular Biology (ISMB), Detroit, MI, 2005.
    [BibTeX] [Download PDF]
    @inproceedings{phuang05:ismb,
    Address = {Detroit, MI},
    Author = {P-H. Huang and V. Pavlovic},
    Booktitle = {Int'l Conf. Intelligent Systems for Molecular Biology (ISMB)},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jun,
    Note = {50\% contribution. Poster. N/A acceptance rate},
    Title = {Protein homology detection using sparse profile hidden {Markov} models},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/phuang05ismb.pdf},
    Year = {2005},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/phuang05ismb.pdf}}

  • B. Kisacanin and V. Pavlovic, “Real-Time Algorithms: From Signal Processing to Computer Vision,” in Real-Time Vision for Human-Computer Interaction, P. V. B. Kisacanin and T. S. Huang, Eds., Springer, 2005, p. 15–40.
    [BibTeX]
    @incollection{kisacanin05:rtvhci,
    Author = {Branislav Kisacanin and Vladimir Pavlovic},
    Booktitle = {Real-Time Vision for Human-Computer Interaction},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Editor = {B. Kisacanin, V. Pavlovic and T.S. Huang},
    Note = {50\% contribution.},
    Pages = {15--40},
    Publisher = {Springer},
    Title = {Real-Time Algorithms: From Signal Processing to Computer Vision},
    Year = {2005}}

  • V. Pavlovic, D. Schonfeld, and G. Friedman, “Stochastic noise process enhancement of Hopfield neural networks,” IEEE Trans. Circuits and Systems II, vol. 52, iss. 4, p. 213–217, 2005. doi:10.1109/tcsii.2004.842027
    [BibTeX] [Download PDF]
    @Article{pavlovic05:tcas2,
    author = {V. Pavlovic and D. Schonfeld and G. Friedman},
    journal = {IEEE Trans. Circuits and Systems II},
    title = {Stochastic noise process enhancement of Hopfield neural networks},
    year = {2005},
    month = apr,
    note = {50\% contribution.},
    number = {4},
    pages = {213--217},
    volume = {52},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic05tcas2.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/tcsii.2004.842027},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic05tcas2.pdf},
    }

2004

  • N. Dandekar and V. Pavlovic, “Multi-species comparative gene identification and analysis of predictive accuracy,” in Gene Finding Workshop at Computational Genomics Conference, Reston, VA, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{dandekar04:cg,
    Address = {Reston, VA},
    Author = {N. Dandekar and V. Pavlovic},
    Booktitle = {Gene Finding Workshop at Computational Genomics Conference},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = oct,
    Note = {50\% contribution. N/A acceptance rate},
    Title = {Multi-species comparative gene identification and analysis of predictive accuracy},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/dandekar04cg.pdf},
    Year = {2004},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/dandekar04cg.pdf}}

  • S. Goldenstein, C. Vogler, J. Stolfi, V. Pavlovic, and D. N. Metaxas, “Outlier rejection in deformable model tracking,” in IEEE Workshop on Articulated and Nonrigid Motion, Washington, DC, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{goldenstein04:cvpr,
    Address = {Washington, DC},
    Author = {S. Goldenstein and C. Vogler and J. Stolfi and V. Pavlovic and D. N. Metaxas},
    Booktitle = {IEEE Workshop on Articulated and Nonrigid Motion},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {20\% contribution. N/A acceptance rate},
    Title = {Outlier rejection in deformable model tracking},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/goldenstein04cvpr.pdf},
    Year = {2004},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/goldenstein04cvpr.pdf}}

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A graphical model based image segmentation method,” in Biomedical Engineering Society Annual Conference, Philadelphia, PA, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{huang04:bme,
    Address = {Philadelphia, PA},
    Author = {Rui Huang and Vladimir Pavlovic and Dimitris N. Metaxas},
    Booktitle = {Biomedical Engineering Society Annual Conference},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = oct,
    Note = {33\% contribution. N/A acceptance rate},
    Title = {A graphical model based image segmentation method},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/huang04bme.pdf},
    Year = {2004},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/huang04bme.pdf}}

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A graphical model framework for coupling MRFs and deformable models,” in Proc. CVPR, Washington, DC, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{huang04:cvpr,
    Address = {Washington, DC},
    Author = {Rui Huang and Vladimir Pavlovic and Dimitris N. Metaxas},
    Booktitle = {Proc. CVPR},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Keywords = {segmentation, graphical models},
    Month = jul,
    Note = {33\% contribution. Poster, 23.6\% acceptance rate.},
    Title = {A graphical model framework for coupling {MRF}s and deformable models},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/huang04cvpr.pdf},
    Year = {2004},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/huang04cvpr.pdf}}

  • R. Huang, V. Pavlovic, and D. N. Metaxas, “A hybrid face recognition method using Markov random fields,” in Int’l Conf. Pattern Recognition, Cambridge, UK, 2004. doi:10.1109/icpr.2004.1334492
    [BibTeX] [Download PDF]
    @InProceedings{huang04:icpr,
    author = {Rui Huang and Vladimir Pavlovic and Dimitris N. Metaxas},
    booktitle = {Int'l Conf. Pattern Recognition},
    title = {A hybrid face recognition method using {Markov} random fields},
    year = {2004},
    address = {Cambridge, UK},
    note = {33\% contribution. Oral presentation, 18.0\% acceptance rate},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/huang04icpr.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/icpr.2004.1334492},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/huang04icpr.pdf},
    }

  • V. Pavlovic, “Model-based motion clustering using boosted mixture modeling,” in Proc. CVPR, Washington, DC, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic04:cvpr,
    Address = {Washington, DC},
    Author = {Vladimir Pavlovic},
    Booktitle = {Proc. CVPR},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jul,
    Note = {100\% contribution. Poster, 23.6\% acceptance rate},
    Title = {Model-based motion clustering using boosted mixture modeling},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic04cvpr.pdf},
    Year = {2004},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic04cvpr.pdf}}

2003

  • J. Alon, S. Sclaroff, G. Kollios, and V. Pavlovic, “Discovering Clusters in Motion Time-Series Data,” in IEEE Conf. Computer Vision and Pattern Recognition, Madison, WI, 2003.
    [BibTeX] [Download PDF]
    @inproceedings{alon03:cvpr,
    Address = {Madison, WI},
    Author = {Joni Alon and Stan Sclaroff and George Kollios and Vladimir Pavlovic},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jun,
    Note = {25\% contribution. Poster, 23.6\% acceptance rate.},
    Title = {Discovering Clusters in Motion Time-Series Data},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/alon03cvpr.pdf},
    Year = {2003},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/alon03cvpr.pdf}}

  • A. Garg, V. Pavlovic, and J. M. Rehg, “Boosted learning in dynamic Bayesian networks for multimodal speaker detection,” Proc. of the IEEE, vol. 91, iss. 9, p. 1355–1369, 2003. doi:10.1109/jproc.2003.817119
    [BibTeX] [Download PDF]
    @Article{garg03:pieee,
    author = {A. Garg and V. Pavlovic and J. M. Rehg},
    journal = PIEEE,
    title = {Boosted learning in dynamic {Bayesian} networks for multimodal speaker detection},
    year = {2003},
    month = sep,
    note = {33\% contribution.},
    number = {9},
    pages = {1355--1369},
    volume = {91},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/garg03pieee.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/jproc.2003.817119},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/garg03pieee.pdf},
    }

  • V. Pavlovic, L. Zhang, C. Cantor, and S. Kasif., “Cross-species gene identification: evolutionary analysis and architectures,” Computational Genomics, 2003.
    [BibTeX]
    @article{pavlovic03:cg,
    Author = {V. Pavlovic and L. Zhang and C. Cantor and S. Kasif.},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Journal = {Computational Genomics},
    Month = oct,
    Note = {30\% contribution. Oral presentation, N/A acceptance rate},
    Title = {Cross-species gene identification: evolutionary analysis and architectures},
    Year = {2003}}

  • J. M. Rehg, V. Pavlovic, T. S. Huang, and W. T. Freeman, “Guest editors’ introduction to the special section on graphical models in computer vision,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, iss. 7, p. 785–786, 2003. doi:10.1109/tpami.2003.1206508
    [BibTeX] [Download PDF]
    @Article{rehg03:pamisi,
    author = {Rehg, J.M. and Pavlovic, V. and Huang, T.S. and Freeman, W.T.},
    journal = TPAMI,
    title = {Guest editors' introduction to the special section on graphical models in computer vision},
    year = {2003},
    month = jul,
    number = {7},
    pages = {785--786},
    volume = {25},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/rehg03pamisi.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/tpami.2003.1206508},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/rehg03pamisi.pdf},
    }

  • Y. Su, T. M. Murali, V. Pavlovic, M. Schaffer, and S. Kasif, “RankGene: Identification of diagnostic genes based on expression data,” Bioinformatics, vol. 19, iss. 12, p. 1578–9, 2003. doi:10.1093/bioinformatics/btg179
    [BibTeX] [Download PDF]
    @Article{suy03:bi,
    author = {Y. Su and T. M. Murali and V. Pavlovic and M. Schaffer and S. Kasif},
    journal = BIO,
    title = {RankGene: Identification of diagnostic genes based on expression data},
    year = {2003},
    month = aug,
    note = {20\% contribution.},
    number = {12},
    pages = {1578--9},
    volume = {19},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/su03bi.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/bioinformatics/btg179},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/su03bi.pdf},
    }

  • L. Zhang, V. Pavlovic, C. Cantor, and S. Kasif., “Human-mouse gene identification by comparative evidence integration and evolutionary analysis,” Genome Research, vol. 13, iss. 6A, p. 1190–202, 2003. doi:10.1101/gr.703903
    [BibTeX] [Download PDF]
    @Article{zhang03:gr,
    author = {L. Zhang and V. Pavlovic and C. Cantor and S. Kasif.},
    journal = {Genome Research},
    title = {Human-mouse gene identification by comparative evidence integration and evolutionary analysis},
    year = {2003},
    month = jun,
    note = {50\% contribution.},
    number = {6A},
    pages = {1190--202},
    volume = {13},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/zhang03gr.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1101/gr.703903},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/zhang03gr.pdf},
    }

2002

  • T. Choudhury, J. M. Rehg, V. Pavlovic, and A. Pentland, “Boosting and Structure Learning in Dynamic “Bayesian” Networks for Audio-Visual Speaker Detection,” in ICPR, Quebec City, Quebec, 2002.
    [BibTeX] [Download PDF]
    @inproceedings{choudhury02:icpr,
    Address = {Quebec City, Quebec},
    Author = {T. Choudhury and J. M. Rehg and V. Pavlovic and A. Pentland},
    Booktitle = {ICPR},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {30\% contribution. Poster, 44.8\% acceptance rate.},
    Title = {Boosting and Structure Learning in Dynamic "{Bayesian}" Networks for Audio-Visual Speaker Detection},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/choudhury02icpr.pdf},
    Year = {2002},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/choudhury02icpr.pdf}}

  • T. Choudhury, J. Rehg, V. Pavlovic, and A. Pentland, “Multimodal speaker detection using boosted dynamic Bayesian networks,” in 1.Int’l Conf. Information Fusion, 2002, p. 550–556.
    [BibTeX]
    @inproceedings{choudhury02:if,
    Author = {T. Choudhury and J. Rehg and V. Pavlovic and A. Pentland},
    Booktitle = {1.Int'l Conf. Information Fusion},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jul,
    Note = {20\% contribution, N/A acceptance rate},
    Pages = {550--556},
    Title = {Multimodal speaker detection using boosted dynamic {Bayesian} networks},
    Year = {2002}}

  • A. Garg and V. Pavlovic, “Bayesian Networks as Ensemble of Classifiers,” in ICPR, Quebec City, Quebec, 2002.
    [BibTeX] [Download PDF]
    @inproceedings{garg02:icpr,
    Address = {Quebec City, Quebec},
    Author = {Ashutosh Garg and Vladimir Pavlovic},
    Booktitle = {ICPR},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {50\% contribution. Oral presentation, 20.2\% acceptance rate},
    Title = {{Bayesian} Networks as Ensemble of Classifiers},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/garg02icpr.pdf},
    Year = {2002},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/garg02icpr.pdf}}

  • M. Walker, V. Pavlovic, and S. Kasif, “A comparative genomic method for computational identification of prokaryotic translation initiation sites,” in RECOMB, 2002. doi:10.1093/nar/gkf423
    [BibTeX]
    @InProceedings{pavlovic02:start-recomb,
    author = {Megon Walker and Vladimir Pavlovic and Simon Kasif},
    booktitle = {RECOMB},
    title = {A comparative genomic method for computational identification of prokaryotic translation initiation sites},
    year = {2002},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/nar/gkf423},
    }

  • V. Pavlovic, A. Garg, and S. Kasif, “A Bayesian framework for combining gene predictions,,” Bioinformatics, vol. 18, iss. 1, p. 19–27, 2002. doi:10.1093/bioinformatics/18.1.19
    [BibTeX] [Download PDF]
    @Article{pavlovic02:bioinf,
    author = {V. Pavlovic and A. Garg and S. Kasif},
    journal = BIO,
    title = {A {Bayesian} framework for combining gene predictions,},
    year = {2002},
    month = nov,
    note = {33\% contribution},
    number = {1},
    pages = {19--27},
    volume = {18},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic02bi.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/bioinformatics/18.1.19},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic02bi.pdf},
    }

  • M. Walker, V. Pavlovic, and S. Kasif, “A comparative genomic method for computational identification of prokaryotic translation initiation sites,” Nucleic Acids Research, vol. 30, iss. 14, p. 3181–91, 2002. doi:10.1093/nar/gkf423
    [BibTeX] [Download PDF]
    @Article{walker02:nar,
    author = {M. Walker and V. Pavlovic and S. Kasif},
    journal = {Nucleic Acids Research},
    title = {A comparative genomic method for computational identification of prokaryotic translation initiation sites},
    year = {2002},
    month = jul,
    note = {33\% contribution.},
    number = {14},
    pages = {3181--91},
    volume = {30},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/walker02nar.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/nar/gkf423},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/walker02nar.pdf},
    }

2001

  • T. Choudhury, J. Rehg, V. Pavlovic, and A. Pentland, “Multimodal speaker detection using boosted dynamic Bayesian networks,” in Snowbird Learning workshop, Snowbird, UT, 2001.
    [BibTeX]
    @inproceedings{choudhury01:snow,
    Address = {Snowbird, UT},
    Author = {T. Choudhury and J. Rehg and V. Pavlovic and A. Pentland},
    Booktitle = {Snowbird Learning workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Title = {Multimodal speaker detection using boosted dynamic {Bayesian} networks},
    Year = {2001}}

  • A. Garg, V. Pavlovic, and J. M. Rehg, “Audio-Visual Speaker Detection using Dynamic Bayesian Networks,” in Int’l Conference on Automatic Face and Gesture Recognition, Grenoble, France, 2001.
    [BibTeX] [Download PDF]
    @inproceedings{garg01:fg,
    Address = {Grenoble, France},
    Author = {Ashutosh Garg and Vladimir Pavlovic and James M. Rehg},
    Booktitle = {Int'l Conference on Automatic Face and Gesture Recognition},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = apr,
    Note = {33\% contribution. N/A acceptance rate.},
    Title = {Audio-Visual Speaker Detection using Dynamic {Bayesian} Networks},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/fg00.pdf},
    Year = {2001},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/fg00.pdf}}

  • V. Pavlovic and A. Garg, “Efficient Detection of Objects and Attributes Using Boosting,” in IEEE Conf. Computer Vision and Pattern Recognition, Kauai, HI, 2001.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic01:cvpr,
    Address = {Kauai, HI},
    Author = {Vladimir Pavlovic and Ashutosh Garg},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = dec,
    Note = {50\% contribution},
    Title = {Efficient Detection of Objects and Attributes Using Boosting},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr01.pdf},
    Year = {2001},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr01.pdf}}

  • V. Pavlovic, D. Schonfeld, and G. Friedman, “Enhancement of Hopfield neural networks using stochatic noise processes,” in Neural Networks for Signal Processing XI, Proc. IEEE Signal Processing Society Workshop, 2001.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic01:nnsp,
    Author = {Vladimir Pavlovic and Dan Schonfeld and Genady Friedman},
    Booktitle = {Neural Networks for Signal Processing XI, Proc. IEEE Signal Processing Society Workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {50\% contribution. Poster, N/A acceptance rate},
    Title = {Enhancement of Hopfield neural networks using stochatic noise processes},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/nnsp01.pdf},
    Year = {2001},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/nnsp01.pdf}}

  • V. Pavlovic and S. Kasif, “Learning improved gene prediction,” in Snowbird Learning workshop, Snowbird, UT, 2001.
    [BibTeX]
    @inproceedings{pavlovic01:snow,
    Address = {Snowbird, UT},
    Author = {Vladimir Pavlovic and Simon Kasif},
    Booktitle = {Snowbird Learning workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Title = {Learning improved gene prediction},
    Year = {2001}}

2000

  • V. Pavlovic, A. Garg, and S. Kasif, “A Bayesian Framework for Combining Gene Predictions,” in Computational Genomics, 2000. doi:10.1093/bioinformatics/18.1.19
    [BibTeX]
    @InProceedings{pavlovic00:cgen,
    author = {Vladimir Pavlovic and Ashutosh Garg and Simon Kasif},
    booktitle = {Computational Genomics},
    title = {A {Bayesian} Framework for Combining Gene Predictions},
    year = {2000},
    month = nov,
    note = {33\% contribution. Oral presentation, N/A acceptance rate},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1093/bioinformatics/18.1.19},
    }

  • V. Pavlovic and J. M. Rehg, “Impact of dynamic model learning on classification of human motion,” in IEEE Conf. Computer Vision and Pattern Recognition, Hilton Head Island, SC, 2000.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic00:cvprmotion,
    Address = {Hilton Head Island, SC},
    Author = {Vladimir Pavlovic and James M. Rehg},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jun,
    Note = {50\% contribution. Oral presentation, 14.2\% acceptance rate.},
    Title = {Impact of dynamic model learning on classification of human motion},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr00slds.pdf},
    Year = {2000},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr00slds.pdf}}

  • V. Pavlovic, A. Garg, J. M. Rehg, and T. S. Huang, “Multimodal speaker detection using error feedback DBNs,” in IEEE Conf. Computer Vision and Pattern Recognition, Hilton Head Island, SC, 2000.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic00:cvprspeaker,
    Address = {Hilton Head Island, SC},
    Author = {Vladimir Pavlovic and Ashutosh Garg and James M. Rehg and Thomas S. Huang},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jun,
    Note = {33\% contribution. Oral presentation, 14.2\% acceptance rate.},
    Title = {Multimodal speaker detection using error feedback {DBNs}},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr00speaker.pdf},
    Year = {2000},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr00speaker.pdf}}

  • V. Pavlovic, A. Garg, and J. M. Rehg, “Multimodal speaker detection using input/output hidden Markov models,” in Int’l Conf. Multimodal Interfaces, Beijing, China, 2000.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic00:icmi,
    Address = {Beijing, China},
    Author = {Vladimir Pavlovic and Ashutosh Garg and James M. Rehg},
    Booktitle = {Int'l Conf. Multimodal Interfaces},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = oct,
    Note = {33\% contribution. Oral presentation, N/A acceptance rate},
    Title = {Multimodal speaker detection using input/output hidden {Markov} models},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/icmi00.pdf},
    Year = {2000},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/icmi00.pdf}}

  • V. Pavlovic, J. M. Rehg, and T. Cham, “A dynamic Bayesian network approach to tracking using learned,” in Int’l Workshop on Hybrid Systems: Computation and Control, Pittsburgh, PA, 2000.
    [BibTeX]
    @inproceedings{pavlovic00:iwhs,
    Address = {Pittsburgh, PA},
    Author = {Vladimir Pavlovic and James M. Rehg and Tat-Jen Cham},
    Booktitle = {Int'l Workshop on Hybrid Systems: Computation and Control},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = mar,
    Note = {33\% contribution. Oral presentation, N/A acceptance rate},
    Title = {A dynamic {Bayesian} network approach to tracking using learned},
    Year = {2000}}

  • V. Pavlovic, J. M. Rehg, and J. MacCormick, “Learning Switching Linear Models of Human Motion,” in Neural Information Processing Systems, Denver, CO, 2000.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic00:nips,
    Address = {Denver, CO},
    Author = {Vladimir Pavlovic and James M. Rehg and John MacCormick},
    Booktitle = {Neural Information Processing Systems},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = nov,
    Note = {33\% contribution. Poster, 30.2\% acceptance rate.},
    Title = {Learning Switching Linear Models of Human Motion},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/nips00.pdf},
    Year = {2000},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/nips00.pdf}}

  • V. Pavlovic and J. M. Rehg, “Learning switching linear system models of figure motion from image sequences,” in Snowbird learning workshop, Snowbird, UT, 2000.
    [BibTeX]
    @inproceedings{pavlovic00:snow,
    Address = {Snowbird, UT},
    Author = {Vladimir Pavlovic and James M. Rehg},
    Booktitle = {Snowbird learning workshop},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Title = {Learning switching linear system models of figure motion from image sequences},
    Year = {2000}}

  • R. Sharma, V. Pavlovic, T. S. Huang, Z. Lo, S. Chu, Y. Zhao, M. Zeller, J. Phillips, and K. Schulten, “Speech/gesture interface to a visual computing environment for molecular biologists,” IEEE Computer Graphics and Applications, vol. 20, iss. 2, p. 29–37, 2000.
    [BibTeX] [Download PDF]
    @article{sharma00:cga,
    Author = {R. Sharma and V. Pavlovic and T.S. Huang and Z. Lo and S. Chu and Y. Zhao and M. Zeller and J. Phillips and K. Schulten},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Journal = {IEEE Computer Graphics and Applications},
    Month = mar,
    Note = {20\% contribution.},
    Number = {2},
    Pages = {29--37},
    Title = {Speech/gesture interface to a visual computing environment for molecular biologists},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/sharma00cg.pdf},
    Volume = {20},
    Year = {2000},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/sharma00cg.pdf}}

1999

  • V. Pavlovic, “Dynamic Bayesian Networks for Information Fusion with Application to Human-Computer Interfaces,” PhD Thesis, 1999.
    [BibTeX] [Download PDF]
    @phdthesis{pavlovic99:phd,
    Author = {Vladimir Pavlovic},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jan,
    School = {University of Illinois at Urbana-Champaign},
    Title = {Dynamic {Bayesian} Networks for Information Fusion with Application to Human-Computer Interfaces},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/phd.pdf},
    Year = {1999},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/phd.pdf}}

  • V. Pavlovic, B. Frey, and T. S. Huang, “Time Series Classification Using Mixed-State Dynamic Bayesian Networks,” in IEEE Conf. Computer Vision and Pattern Recognition, Ft. Collins, CO, 1999.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic99:cvpr,
    Address = {Ft. Collins, CO},
    Author = {Vladimir Pavlovic and Brendan Frey and Thomas S. Huang},
    Booktitle = CVPR,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {33\% contribution. Oral presentation, N/A acceptance rate.},
    Title = {Time Series Classification Using Mixed-State Dynamic {Bayesian} Networks},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr99.pdf},
    Year = {1999},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/cvpr99.pdf}}

  • V. Pavlovic, J. M. Rehg, T. Cham, and K. Murphy, “A Dynamic Bayesian Network Approach to Figure Tracking Using Learned Dynamical Models,” in IEEE Int’l Conf. Computer Vision, Kerkyra, Greece, 1999. doi:10.1109/iccv.1999.791203
    [BibTeX] [Download PDF]
    @InProceedings{pavlovic99:iccv,
    author = {Vladimir Pavlovic and James M. Rehg and Tat-Jen Cham and Kevin Murphy},
    booktitle = ICCV,
    title = {A Dynamic {Bayesian} Network Approach to Figure Tracking Using Learned Dynamical Models},
    year = {1999},
    address = {Kerkyra, Greece},
    month = oct,
    note = {25\% contribution. Oral presentation, 31\% acceptance rate.},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/iccv99.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/iccv.1999.791203},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/iccv99.pdf},
    }

  • V. Pavlovic, B. Frey, and T. S. Huang, “Variational Learning in Mixed-State Dynamic Graphical Models,” in Proc. Uncertainty in Artificial Intelligence, Stockholm, Sweeden, 1999.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic99:uai,
    Address = {Stockholm, Sweeden},
    Author = {Vladimir Pavlovic and Brendan Frey and Thomas S. Huang},
    Booktitle = {Proc. Uncertainty in Artificial Intelligence},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = aug,
    Note = {33\% contribution. Oral presentation, 51\% acceptance rate.},
    Title = {Variational Learning in Mixed-State Dynamic Graphical Models},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/uai99.ps.gz},
    Year = {1999},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/uai99.ps.gz}}

  • V. Pavlovic, P. Moulin, and K. Ramchandran, “Integrated framework for adaptive subband image coding,” IEEE Transactions on Signal Processing, vol. 47, iss. 4, p. 1024–1038, 1999. doi:10.1109/78.752600
    [BibTeX] [Download PDF]
    @Article{pavlovic99:tsp,
    author = {V. Pavlovic and P. Moulin and K. Ramchandran},
    journal = {IEEE Transactions on Signal Processing},
    title = {Integrated framework for adaptive subband image coding},
    year = {1999},
    month = apr,
    note = {33\% contribution.},
    number = {4},
    pages = {1024--1038},
    volume = {47},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic99sp.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/78.752600},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic99sp.pdf},
    }

1998

  • G. Berry, V. Pavlovic, and T. S. Huang, “A Multimodal Human-Computer Interface for the Control of a Virtual Environment,” in AAAI Workshop on Intelligent Environments, Stanford University, CA, 1998.
    [BibTeX] [Download PDF]
    @inproceedings{berry98:aaai,
    Address = {Stanford University, CA},
    Author = {Gregory Berry and Vladimir Pavlovic and Thomas S. Huang},
    Booktitle = {AAAI Workshop on Intelligent Environments},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {33\% contribution. N/A acceptance rate},
    Title = {A Multimodal Human-Computer Interface for the Control of a Virtual Environment},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/aaai98ie.pdf},
    Year = {1998},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/aaai98ie.pdf}}

  • V. Pavlovic and T. S. Huang, “Multimodal Tracking and Classification of Audio-Visual Features,” in AAAI Workshop on Representations for Multi-modal Human-Computer Interaction, Madison, WI, 1998.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic98:aaai,
    Address = {Madison, WI},
    Author = {Vladimir Pavlovic and Thomas S. Huang},
    Booktitle = {AAAI Workshop on Representations for Multi-modal Human-Computer Interaction},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jul,
    Note = {50\% contribution. Oral presentation, N/A acceptance rate},
    Title = {Multimodal Tracking and Classification of Audio-Visual Features},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/aaai98mm.pdf},
    Year = {1998},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/aaai98mm.pdf}}

  • V. Pavlovic, G. Berry, T. S. Huang, L. Devi, Y. Sethi, and R. Sharma, “Integration of speech and gestures for display control,” in 2nd Advanced Display Federated Laboratory Symposium, College Park, MD, 1998.
    [BibTeX]
    @inproceedings{pavlovic98:arl,
    Address = {College Park, MD},
    Author = {V. Pavlovic and G. Berry and T.S. Huang and L. Devi and Y. Sethi and R. Sharma},
    Booktitle = {2nd Advanced Display Federated Laboratory Symposium},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = feb,
    Title = {Integration of speech and gestures for display control},
    Year = {1998}}

  • V. Pavlovic and T. S. Huang, “Tracking and classification of audio/visual features,” in IEEE Int’l Conf. Image Processing, Chicago, IL, 1998.
    [BibTeX]
    @inproceedings{pavlovic98:icip,
    Address = {Chicago, IL},
    Author = {Vladimir Pavlovic and Thomas S. Huang},
    Booktitle = ICIP,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {50\% contribution. Poster, N/A acceptance rate},
    Title = {Tracking and classification of audio/visual features},
    Year = {1998}}

  • R. Sharma, V. Pavlovic, and T. S. Huang, “Towards multimodal human-computer interface,” Proc. of the IEEE, vol. 86, iss. 5, p. 853–869, 1998. doi:10.1109/5.664275
    [BibTeX]
    @Article{sharma98:pieee,
    author = {R. Sharma and V. Pavlovic and T. S. Huang},
    journal = PIEEE,
    title = {Towards multimodal human-computer interface},
    year = {1998},
    month = may,
    note = {33\% contribution.},
    number = {5},
    pages = {853--869},
    volume = {86},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/5.664275},
    }

1997

  • V. Pavlovic, K. Ramchandran, and P. Moulin, “Transform image coding based on joint adaptation of filer banks, tree structures and quantizers,” in DCC, Salt Lake City, UT, 1997.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic97:dcc,
    Address = {Salt Lake City, UT},
    Author = {Vladimir Pavlovic and Kanan Ramchandran and Pierre Moulin},
    Booktitle = {DCC},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Title = {Transform image coding based on joint adaptation of filer banks, tree structures and quantizers},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/dcc97.ps.gz},
    Year = {1997},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/dcc97.ps.gz}}

  • V. Pavlovic, G. Berry, and T. S. Huang, “Integration of audio/visual information for intelligent human-computer interaction,” in IEEE Int’l Conf. Image Processing, Santa Barbara, CA, 1997.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic97:icip,
    Address = {Santa Barbara, CA},
    Author = {Vladimir Pavlovic and Gregory Berry and Thomas S. Huang},
    Booktitle = ICIP,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {33\% contribution. Oral presentation, N/A acceptance rate},
    Title = {Integration of audio/visual information for intelligent human-computer interaction},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/icip97.ps.gz},
    Year = {1997},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/icip97.ps.gz}}

  • V. Pavlovic, G. Berry, and T. S. Huang, “Fusion of audio/visual information for human-computer interaction,” in Workshop on Perceptual User Interfaces, Banff, Alberta, 1997.
    [BibTeX] [Download PDF]
    @inproceedings{pavlovic97:pui,
    Address = {Banff, Alberta},
    Author = {Vladimir Pavlovic and Gregory Berry and Thomas S. Huang},
    Booktitle = {Workshop on Perceptual User Interfaces},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = oct,
    Note = {33\% contribution. Poster, N/A acceptance rate},
    Title = {Fusion of audio/visual information for human-computer interaction},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/pui97.pz.gz},
    Year = {1997},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/pui97.pz.gz}}

  • M. Zeller, J. Phillips, A. Dalke, W. Humphrey, K. Schulten, R. Sharma, T. S. Huang, V. Pavlovic, Y. Zhao, Z. Lo, and S. Chu, “A visual computing environment for very large scale biomolecular modeling,” in IEEE International Conference on Application-Specific System, Architectures and Processors, Zurich, Switzerland, 1997.
    [BibTeX]
    @inproceedings{zeller97,
    Address = {Zurich, Switzerland},
    Author = {M. Zeller and J. Phillips and A. Dalke and W. Humphrey and K. Schulten and R. Sharma and T.S. Huang and V. Pavlovic and Y. Zhao and Z. Lo and S. Chu},
    Booktitle = {IEEE International Conference on Application-Specific System, Architectures and Processors},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = jul,
    Title = {A visual computing environment for very large scale biomolecular modeling},
    Year = {1997}}

  • V. Pavlovic, R. Sharma, and T. S. Huang, “Visual interpretation of hand gestures for human-computer interaction: A review,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, iss. 7, p. 677–695, 1997. doi:10.1109/34.598226
    [BibTeX] [Download PDF]
    @Article{pavlovic97:pami,
    author = {V. Pavlovic and R. Sharma and T.S. Huang},
    journal = TPAMI,
    title = {Visual interpretation of hand gestures for human-computer interaction: A review},
    year = {1997},
    month = jul,
    note = {33\% contribution.},
    number = {7},
    pages = {677--695},
    volume = {19},
    bdsk-url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic97pami.pdf},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/34.598226},
    url = {http://www.cs.rutgers.edu/~vladimir/pub/pavlovic97pami.pdf},
    }

1996

  • T. S. Huang, V. Pavlovic, and R. Sharma, “Speech/gesture-based human computer interface in virtual environments,” in Workshop on Integration of Gestures, Speech, and Language, Wilmington, DE, 1996.
    [BibTeX]
    @inproceedings{huang96:wigsl,
    Address = {Wilmington, DE},
    Author = {Thomas S. Huang and Vladimir Pavlovic and Rajeev Sharma},
    Booktitle = {Workshop on Integration of Gestures, Speech, and Language},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = oct,
    Note = {33\% contribution. N/A acceptance rate},
    Title = {Speech/gesture-based human computer interface in virtual environments},
    Year = {1996}}

  • P. Moulin, K. Ramchandran, and V. Pavlovic, “Transform image coding based on joint adaptation of filer banks and tree structures,” in IEEE Int’l Conf. Image Processing, Laussanne, Switzerland, 1996.
    [BibTeX] [Download PDF]
    @inproceedings{moulin96:icip,
    Address = {Laussanne, Switzerland},
    Author = {Pierre Moulin and Kannan Ramchandran and Vladimir Pavlovic},
    Booktitle = ICIP,
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {33\% contribution. Oral presentation, N/A acceptance rate.},
    Title = {Transform image coding based on joint adaptation of filer banks and tree structures},
    Url = {http://www.cs.rutgers.edu/~vladimir/pub/icip96.ps.gz},
    Year = {1996},
    Bdsk-Url-1 = {http://www.cs.rutgers.edu/~vladimir/pub/icip96.ps.gz}}

  • V. Pavlovic, R. Sharma, and T. S. Huang, “Gestural interface to a visual computing environment for molecular biologists,” in 2nd International. Conference on Automatic Face and Gesture Recognition, Killington, VT, 1996.
    [BibTeX]
    @inproceedings{pavlovic96:fg,
    Address = {Killington, VT},
    Author = {Vladimir Pavlovic and Rajeev Sharma and Thomas S. Huang},
    Booktitle = {2nd International. Conference on Automatic Face and Gesture Recognition},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Note = {33\% contribution. Poster, N/A acceptance rate.},
    Title = {Gestural interface to a visual computing environment for molecular biologists},
    Year = {1996}}

  • R. Sharma, T. S. Huang, V. Pavlovic, K. Schulten, A. Dalke, J. Phillips, M. Zeller, W. Humphrey, Y. Zhao, Z. Lo, and S. Chu, “Speech / gesture interface to a visual computing environment for molecular biologists,” in International Conference on Pattern Recognition, Vienna, Austria, 1996. doi:10.1109/icpr.1996.547311
    [BibTeX]
    @InProceedings{sharma96:icpr,
    author = {Rajeev Sharma and Thomas S. Huang and Vladimir Pavlovic and Klauss Schulten and Andrew Dalke and J. Phillips and M. Zeller and W. Humphrey and Y. Zhao and Z. Lo and S. Chu},
    booktitle = {International Conference on Pattern Recognition},
    title = {Speech / gesture interface to a visual computing environment for molecular biologists},
    year = {1996},
    address = {Vienna, Austria},
    date-added = {2012-12-07 19:58:34 +0000},
    date-modified = {2012-12-07 19:58:34 +0000},
    doi = {10.1109/icpr.1996.547311},
    }

  • R. Sharma, T. S. Huang, and V. Pavlovic, “A multimodal framework for interacting with complex virtual environments,” in Human Interaction with Complex Systems, C. A. Ntuen and E. H. Park, Eds., Kluwer Academic Publishers, 1996, p. 53–71.
    [BibTeX]
    @incollection{sharma96:hics,
    Author = {R. Sharma and T. S. Huang and V. Pavlovic},
    Booktitle = {Human Interaction with Complex Systems},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Editor = {C.A. Ntuen and E. H. Park},
    Note = {33\% contribution.},
    Pages = {53--71},
    Publisher = {Kluwer Academic Publishers},
    Title = {A multimodal framework for interacting with complex virtual environments},
    Year = {1996}}

  • R. Sharma, T. S. Huang, and V. Pavlovic, “Human Interaction with Complex Systems,” , C. A. Ntuen and E. H. Park, Eds., Kluwer Academic Publishers, 1996, p. 53–71.
    [BibTeX]
    @inbook{sharma96:book,
    Author = {Rajeev Sharma and Thomas S. Huang and Vladimir Pavlovic},
    Chapter = {A multimodal framework for interacting with complex virtual environments},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Editor = {C. A. Ntuen and E. H. Park},
    Pages = {53--71},
    Publisher = {Kluwer Academic Publishers},
    Title = {Human Interaction with Complex Systems},
    Year = {1996}}

1995

  • T. S. Huang and V. Pavlovic, “Hand gesture modeling, analysis, and synthesis,” in Int’l Workshop on Automatic Face and Gesture Recognition, Zurich, Switzerland, 1995.
    [BibTeX]
    @inproceedings{huang95:fg,
    Address = {Zurich, Switzerland},
    Author = {Thomas S. Huang and Vladimir Pavlovic},
    Booktitle = {Int'l Workshop on Automatic Face and Gesture Recognition},
    Date-Added = {2012-12-07 19:58:34 +0000},
    Date-Modified = {2012-12-07 19:58:34 +0000},
    Month = may,
    Note = {50\% contribution. N/A acceptance rate.},
    Title = {Hand gesture modeling, analysis, and synthesis},
    Year = {1995}}

  • H. X. Pham, Y. Wang, and V. Pavlovic, Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network.
    [BibTeX]
    @unpublished{hai19tac,
    Author = {Hai Xuan Pham and Yuting Wang and Vladimir Pavlovic},
    Date-Added = {2019-09-05 21:05:51 +0100},
    Date-Modified = {2019-09-09 16:39:27 -0400},
    Note = {Under review},
    Title = {Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network}}

  • B. Gholami, O. Rudovic, K. Bousmalis, and V. Pavlovic, Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach.
    [BibTeX]
    @unpublished{gholami19tip,
    Author = {Behnam Gholami and Ognjen Rudovic and Konstantinos Bousmalis and Vladimir Pavlovic},
    Date-Added = {2019-09-05 21:00:52 +0100},
    Date-Modified = {2019-09-05 21:02:05 +0100},
    Note = {under review},
    Title = {Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach}}