Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences


UC Berkeley


Joint Colloquium Distinguished Lecture Series

Probabilistic Models for Holistic Scene Understanding

Daphne KollerWednesday, May 13, 2009
306 Soda Hall (HP Auditorium)
4:00 - 5:00 pm

Daphne Koller
Professor of Computer Science, Stanford University


Over recent years, computer vision has made great strides towards annotating parts of an image with symbolic labels, such as object categories or segment types.  However, we are still far from the ultimate goal of providing a semantic description of an image, such as "a man, walking a dog on a sidewalk, carrying a backpack".  In this talk, I will describe some projects that use probabilistic models in an attempt to move us a little closer towards this goal.

The first part of the talk will present methods that use a more holistic scene analysis to improve our performance at core tasks such as object detection, segmentation, or 3D reconstruction.   The second part of the talk will focus on finer-grained modeling of object shape, so as to allow us to annotate images with descriptive labels related to the object shape, pose, or activity (e.g., is a cheetah running or standing).   These vision tasks rely on novel algorithms for core problems in machine learning and probabilistic models, such as efficient algorithms for probabilistic correspondence, transfer learning across related object classes for learning from sparse data, and more.


Daphne Koller is a Professor of Computer Science at Stanford University.  Her main research focus is in developing and using machine learning and probabilistic methods to model and analyze complex systems, and she is particularly interested in using these techniques to understand biological systems and the world around us.  Professor Koller is the author of over 100 refereed publications, which have appeared in venues that include Science, Nature Genetics, and the Journal of Games and Economic Behavior.  She is a Fellow of the American Association for Artificial Intelligence, and has received a number of awards, including the Sloan Foundation Faculty Fellowship in 1996, the ONR Young Investigator Award in 1998, the Presidential Early Career Award for Scientists and Engineers (PECASE) from President Clinton in 1999, the IJCAI Computers and Thought Award in 2001, the Cox Medal for excellence in fostering undergraduate research at Stanford in 2003, the MacArthur Foundation Fellowship in 2004 and the first-ever ACM/Infosys award in 2008.

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