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Research Area:

Computer Vision

Description

Problems in vision reside at the interface of the physical world, computational machines, and the human brain. Our computational models of the physical world are, by necessity, incomplete, which means that when we observe or act upon the world we do so with inaccurate, uncertain, and ambiguous information.

Research on vision at Brown focuses on this problem of forming and testing hypotheses about a world of which we are uncertain, often from data that are inaccurate, noisy, or inconsistent. Our research includes video motion analysis, tracking, event recognition, object inference and understanding, human motion understanding, and applications of vision in computer graphics. Our work spans many disciplines and involves collaborations with researchers in Engineering, Neuroscience, Cognitive and Linguistic Sciences, Mathematics, Applied Mathematics, and Biomechanics. Our facilities include a Vicon motion-capture system and high-speed multi-camera video capture equipment.

Faculty

Michael J. Black
John F. Hughes
Chad Jenkins

Topics or Projects

Markov Random Fields
Subspace Learning
Markerless Motion Capture
Layered Representation of the Visual World
Graphical Models
Belief Propagation
Human Motion Understanding
Human Motion Estimation
Structure from Motion
Shape from Texture
Optical Flow
Video Databases
Anisotropic Diffusion
Visual Psychophysics
Computer Vision
Image Denoising
Image Statistics
Facial Expression Recognition
Mixture Models
Tracking
Specular Motion
Bayesian Inference
Human Pose Detection
Robust Statistics
Particle Filtering
Image Segmentation
Motion Discontinuities

Page Owner: Michael Black Last Modified: Wed Jun 27 12:26:37 2007