Parsing Images (Distinguished Lecture)

Speaker: Prof. Jitendra Malik, UC Berkeley
Host: Prof. Ram NevatiaAbstract:
When humans look at an image or a video clip, they start from the raw input, a collection of pixels, and infer considerable structure and semantics about the world that is projected into the image. They construct a hierarchical partition of the image into sets of pixels that correspond to "objects" or "parts" of objects, and attach concepts - "dog", "forest" etc to various levels in this hierarchy. We have considerable evidence from perception that this process is based on bottom up cues such as similarity of pixel brightness, color, texture and motion as well as top down input derived from familiar visual categories such as faces or street scenes. Constructing a computational model for this is perhaps the central problem in both human and machine vision. Various subproblems of this grand challenge include image segmentation, perceptual grouping and visual recognition.My research group and I have been studying different aspects of this problem for more than a decade, and at this stage, we feel we have the outlines of a framework for solving it. We start with a local process of marking contours in images based on local differences in brightness, color, texture etc, move on to a more global framework for extracting coherent regions, which in turn help drive a process of visual recognition, which then feedback to refine the grouping itself. We can quantify the performance of the framework on various standard datasets for the subproblems. Of course, much more work needs to be done to attain human level performance, but I feel optimistic that computer vision is on track towards closing the much-cited ``semantic gap'' between pixels and perception.Biography:
Jitendra Malik was born in Mathura, India in 1960. He received the B.Tech degree in Electrical Engineering from Indian Institute of Technology, Kanpur in 1980 and the PhD degree in Computer Science from Stanford University in 1985. In January 1986, he joined the university of California at Berkeley, where he is currently the Arthur J. Chick Professor in the Computer Science Division, Department of Electrical Engg and Computer Sciences. He is also on the faculty of the Cognitive Science and Vision Science groups. During 2002-2004 he served as the Chair of the Computer Science Division and during 2004-2006 as the Department Chair of EECS. He serves on the advisory board of Microsoft Research India, and on the Governing Body of IIIT Bangalore.His current research interests are in computer vision, computational modeling of human vision and analysis of biological images. His work has spanned a range of topics in vision including image segmentation, perceptual grouping, texture, stereopsis and object recognition with applications to image based modeling and rendering in computer graphics, intelligent vehicle highway systems, and biological image analysis. He has authored or co-authored more than a hundred and fifty research papers on these topics, and graduated twenty-five PhD students who occupy prominent places in academia and industry.He received the gold medal for the best graduating student in Electrical Engineering from IIT Kanpur in 1980, a Presidential Young Investigator Award in 1989, and the Rosenbaum fellowship for the Computer Vision Programme at the Newton Institute of Mathematical Sciences, University of Cambridge in 1993. At UC Berkeley, he was selected for the Diane S. McEntyre Award for Excellence in Teaching in 2000, a Miller Research Professorship in 2001, and appointed to be the Arthur J. Chick Professor in 2002. He received the Distinguished Alumnus Award from IIT Kanpur in 2008. He was awarded the Longuet-Higgins Prize for a contribution that has stood the test of time twice, in 2007 and in 2008. He is a fellow of the IEEE.

Location: Seaver Science Library (SSL) - 150

Audiences: Everyone Is Invited

Contact: CS Colloquia