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Shape Analysis for Imaging Understanding

SpeakerDr. Washington Mio
Organization Florida State University, Dept of Mathematics
Location316 EGRC
Start Date December 10, 2003 11:00 AM
End Date

We discuss a new framework for the representation and quantitative analysis of planar shapes and applications to the automated recognition and classification of objects in digital images. Shape extraction is particularly challenging in imagery involving partial occlusions of objects, noise, or low contrast. We take a Bayesian approach to the problem, which requires the development of image models encoding prior knowledge of shapes. This involves the problem of clustering shapes and "learning" probability models for observed shapes in addition to considerations of pixel models.

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