Sequence Analysis and Modeling Lab
1. Abstract
Traditional computer vision algorithms, particularly those that exploit various probabilistic and learning-based approaches, are often formulated in centralized settings. However, modern computational settings are becoming increasingly characterized by networks of peer-to-peer connected devices, with local data processing abilities. … Read the rest
Recognition of Ancient Roman Coins
1. Problem Formulation
For a given Roman coin image, the goal is to recognize who is on the coin
<!–
There are thousand of different ways to define the Roman coins. For example, we can … Read the rest
1. Abstract
Tracking human faces has remained an active research area among the computer vision community for a long time due to its usefulness in a number of applications, such as video surveillance, expression analysis and human-computer interaction. An automatic … Read the rest
*Chongyu Chen was with Nanyang Technological University*
1. Abstract.
Existing depth recovery methods for commodity RGB-D sensors primarily rely on low-level information for repairing the measured depth estimates. However, as the distance of the scene from the camera increases, the … Read the rest
A result sample of our 3D face tracker, where (a) shows the 3D landmarks projected onto image plane, (b,c) show the 3D blendshape model and the input point cloud, and (d) shows the skinned 3D shape.
1. Abstract.
We introduce … Read the rest
Abstract
Video segmentation is a stepping stone to understanding video context. Video segmentation enables one to represent a video by decomposing it into coherent regions which comprise whole or parts of objects. However, the challenge originates from the fact that … Read the rest
Sea level prediction is a complicated spatial temporal regression problem that draw a lot of attention these days. Understanding sea level behavior can help us know more about climate change and consequent effects. However, predicting sea level is not really … Read the rest
The research I have been working on is String Kernel Methods for DNA sequence analysis, under the supervision of Prof. Pavlovic. I focus on the problem of species-level identification based on short DNA fragments known as barcodes. Kernel methods approach … Read the rest
Problem Definition
Financial decisions with respect to investing in industry based indices are often based on heuristics and non-standard methods or purely based on the company specific algorithmic methods. In-depth analysis of the historic stock market behavior and dynamics among … Read the rest
Conditional Random Fields (CRFs) and Hidden Conditional Random Fields (HCRFs) are a staple of many sequence tagging and classification frameworks. An underlying assumption in those models is that the state sequences (tags), observed or latent, take their values from a … Read the rest