In this work we present Discriminative Random Fields (DRFs), a discriminative framework for the classification of image regions by incorporating neighborhood interactions in the l...
Several geometric active contour models have been proposed for segmentation in computer vision. The essential idea is to evolve a curve (in 2D) or a surface (in 3D) under constrai...
This work takes place in the context of hierarchical stochastic models for the resolution of discrete inverse problems from low level vision. Some of these models lie on the nodes...
We introduce a finite difference expansion for closely spaced cameras in projective vision, and use it to derive differential analogues of the finite-displacement projective match...
Representing shapes is a signi cant problem for vision systems that must recognize or classify objects. We derive a representation for a given shape by investigating its self-simi...