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Shape Estimation and Object Classification in Images Using Geometric Priors

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2 Author(s)
Shantanu H. Joshi ; Department of Electrical and Computer Engineering, Florida State University, Tallahassee, Florida 32310. Email: ; Anuj Srivastava

We propose a method for modeling and incorporating prior shape information for Bayesian shape estimation from images. In this approach, shapes are treated as elements of an infinite-dimensional, non-linear, quotient space. Prior probability models on shape classes are defined and computed intrinsically on the tangent bundle of this shape space. MAP shape estimation is posed as a problem of gradient-based energy minimization where this energy has contributions from the image data and the prior model.

Published in:

2006 Fortieth Asilomar Conference on Signals, Systems and Computers

Date of Conference:

Oct. 29 2006-Nov. 1 2006