UTCS AI Colloquia - Dr. Xiaofeng Ren, Research Scientist, Intel Labs, "RGB-D Perception: Solving Real-World Computer Vision with Consumer Depth Cameras"

Contact Name: 
Craig Corcoran
Location: 
ACE 2.402
Date: 
Jan 24, 2013 1:00pm - 2:00pm

Signup Schedule: http://apps.cs.utexas.edu/talkschedules/cgi/list_events.cgi

Talk Audience: UTCS Faculty, Grads, Undergrads, Other Interested Parties

Host: Kristen Grauman

Talk Abstract: Kinect-style depth cameras offer real-time synchronized color and depth data in a convenient package at a consumer price. Such RGB-D cameras are dramatically changing the research and application landscapes of vision, robotics and HCI. I will take you through our journey of investigating and promoting the joint uses of color and depth toward rich sensing solutions under real-world conditions, from 3D modeling of indoor environments to fine-grained recognition of objects, scenes and activities. Our main approach is feature learning, designing and learning rich features in hierarchical structures that seamlessly apply to both color and depth. Our work on hierarchical matching pursuit uses efficient sparse coding algorithms, namely Orthogonal Matching Pursuit and K-SVD, as building blocks to extract rich features at varying scales and deformations, outperforming hand-designed features by large margins on both color and RGB-D object recognition. Such learned features also help to improve the states of the art on a variety of tasks such as scene classification, labeling and segmentation. RGB-D perception shines in both robustness and efficiency, on the fast track of becoming the general sensing solution for future pervasive and context-aware systems.

Speaker Bio: Xiaofeng Ren is a research scientist at Intel Labs and an affiliate assistant professor at the University of Washington. His research interests are broadly in the areas of computer vision and its applications, including image features, grouping and segmentation, object recognition, scene understanding, and video analysis. His current focus is on understanding and solving computer vision problems in everyday life settings. He received his Ph.D. from University of California, Berkeley and his B.S. from Zhejiang University. Prior to joining Intel in 2008, he was on the research faculty of Toyota Technological Institute at Chicago.

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