[Colloquium] TTI-C Colloquium: Yali Amit, U of C

[Julia MacGlashan]

*REMINDER*

When:             *Monday, Nov 16 @ 1:00pm*

Where:           * TTI-C Conference Room #526*, 6045 S Kenwood Ave

Who:               *Yali Amit*, University of Chicago, CS Department

Title:          *      **Statistical Models in Computer Vision*


The goal of Computer Vision is the automatic labeling of images containing
multiple objects as well as noise and clutter. Recent work has focused on
two main tasks. The first is the classification among object classes in
segmented images containing only one object and the second is the detection
of a particular object class in a large image. Both tasks have been
primarily addressed using discriminative learning. It is not clear however
how these methods can extend to deal with the recognition of multiple object
classes in images containing a number of objects in a wide range of
configurations. I will present an approach which starts from simple
statistical models for individual objects. With these models the important
notion of invariance can be clearly formulated. Furthermore the individual
object models can be composed to define models for object configurations.
Decisions are likelihood based and do not depend on pretrained decision
boundaries. I will briefly discuss some computational strategies for
computing the scene annotation, show some applications, and describe some
major difficulties we face in making further progress.


Contact:          David McAllester, TTI-C       <nati at tti-c.org>
mcallester at tti-c.org <nati at tti-c.org> <nati at tti-c.org>              834-2550
Speaker Schedule: http://www.tti-c.org/colloquium.php
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