UTCS Colloquia/AI: Pedro F. Felzenszwalb/University of Chicago: "Object Recognition with Part-Based Models" ACES 2.402, Friday, March 6, 2009 11:00 a.m.
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Type of Talk: UTCS Colloquium/AI
ation: Pedro F. Felzenszwalb/University of Chicago
/Time: Friday, March 6, 2009 11:00 a.m.
p; ACES 2.402
Host: Kristen Grauman
;Object Recognition with Part-Based Models"
Talk Abstract: &nb
Object recognition is one of the most important and challenging
problems in computer vision. One of the main difficulties is in developing
representations that can effectively capture typical variations in appeara
nce that occur within a class of objects. Deformable part-based models prov
ide a natural and elegant framework for addressing this problem. However,
they also lead to difficult computational problems. I will describe efficie
nt algorithms we have developed for finding objects in images using deforma
ble part-based models. I will also describe a set of techniques we have dev
eloped for training part-based models from weakly labeled data, using a fo
rmalism we call latent SVM. We have used these methods to implement a state
-of-the-art system for finding objects from a generic category, such as pe
ople or cars, in cluttered images.
zwalb is an associate professor in the Department of Computer Science at th
e University of Chicago. His research focuses on computer vision, algorith
ms and artificial intelligence. He received his PhD in computer science fro
m MIT in 2003.
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