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» Covariant Derivatives and Vision
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ICCV
2003
IEEE
15 years 12 months ago
Discriminative Random Fields: A Discriminative Framework for Contextual Interaction in Classification
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...
Sanjiv Kumar, Martial Hebert
ICCV
2001
IEEE
15 years 12 months ago
Flux Maximizing Geometric Flows
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...
Alexander Vasilevskiy, Kaleem Siddiqi
ICCV
1999
IEEE
15 years 12 months ago
Unsupervised Image Classification with a Hierarchical EM Algorithm
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...
Annabelle Chardin, Patrick Pérez
ICCV
1999
IEEE
15 years 12 months ago
Differential Matching Constraints
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...
Bill Triggs
ICCV
1998
IEEE
15 years 12 months ago
Representation and Self-Similarity of Shapes
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...
Tyng-Luh Liu, Davi Geiger, Robert Kohn