We consider the problem of learning density mixture models for Classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent the density at all points in the sample space. Discriminative learning, on the other hand, aims

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Marginal Nonlinear Dynamic System (MNDS) [1]

The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. To automate the process of motion modeling we consider a class of learned dynamic models cast in the framework … Read the rest

Videos

10-2	dudek
trellis 70	Al Pacino
Angelina Jolie	Bill Gates
Jodie Foster	Julia Roberts
Steven Spielberg	Tony Blair
Tracking and Recognition – Bill Clinton	Tracking and Recognition – Jodie Foster
Tracking and Recognition – Tony Blair

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Video-based Face Tracking and Recognition with Visual Constraints [1]

We address the problem of tracking and recognition of faces in real-world, noisy videos. We identify faces using a tracker that adaptively builds the target model reflecting changes in appearance, typical … Read the rest

Image segmentation is one of the most important steps leading to the analysis of image data. The goal is dividing the image into parts that have homogeneous attributes, and have a strong correlation with objects or areas of the real … Read the rest

Shape analysis is an important process for many computer vision applications, including image classification, recognition, retrieval, registration, segmentation, etc. An ideal shape model should be both invariant to global transformations and robust to local distortions. In this work we developed … Read the rest

Nonlinear Dimensionality Reduction for Regression [1]

The task of dimensionality reduction for regression (DRR) is to find a low dimensional representation, z (q-dim), of the input covariates, x (p-dim), with q << p, for regressing the output, y (d-dim), given … Read the rest

Gaussian Process Manifold Kernel Dimensionality Reduction (GPMKDR) [1]

Constructing optimal regressors is an important task in computer vision. Problems such as tracking, 3D human and general object pose estimation, image and signal denoising, illumination direction estimation are but some of … Read the rest

Discriminative Graphical Models

In Collaboration with Dr. James M. Rehg and Yushi Jing, College of Computing, Georgia Institute of Technology.

Discriminative learning, or learning for classification, is a common learning task that has been addressed in a number of different … Read the rest

 

The brain mechanisms underlying the ability of humans to process faces have been studied extensively in the last two decades. Brain imaging techniques, particularly fMRI (functional Magnetic Resonance Imaging) that possesses high spatial resolution but limited temporal resolution, are advancing … Read the rest