CSAIL Event Calendar
Object Category Modeling, Learning, and Recognition by Stochastic GrammarSpeaker: Song-Chun Zhu, Professor, University of California, Los Angeles Date: Thursday, May 31 2007 Time: 2:00PM to 3:00PM Refreshments: 1:45PM Location: Star Seminar Room (32-D463) Host: C. Mario Christoudias, Gerald Dalley, MIT CSAIL Contact: C. Mario Christoudias, Gerald Dalley, 3-4278, 3-6095, cmch@csail.mit.edu, dalleyg@mit.edu Relevant URL: http://www.stat.ucla.edu/~sczhu/papers/Grammar_quest.pdfIn this talk, I will review and discuss some recent progress in my group on object category recognition and parsing. I will introduce a stochastic context sensitive grammar as a unified framework for object modeling, learning and recognition. This grammar is embodied in an And-Or graph representation integrating (i) a hierarchic decomposition to account for structural variations, and (ii) a set of horizontal relations for spatial and functional contexts. Then each object category is defined as the set of all valid configurations produced by its grammar. Then a probabilistic model is defined on the And-Or graph to account for the natural frequency of object instances. This model can be learned from a small training set and simulated through MCMC sampling to generalize to a large number of novel configurations so that they cover unforeseen instances in testing images. To make this grammar model scalable, we have constructed a large manually annotated image database at Lotus Hill Institute to support the learning and evaluation. We also developed a recursive algorithm for bottom-up / top-down inference. I will show some case studies on modeling clothes, man-made objects, and object categories.
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