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17 years 2 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
116
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CVPR
2005
IEEE
16 years 5 months ago
Scene-Adapted Structured Light
In order to overcome several limitations of structured light 3D acquisition methods, the colors, intensities, and shapes of the projected patterns are adapted to the scene. Based ...
Thomas P. Koninckx, Pieter Peers, Philip Dutr&eacu...
160
Voted
CVPR
2006
IEEE
16 years 5 months ago
A Framework for Feature Selection for Background Subtraction
Background subtraction is a widely used paradigm to detect moving objects in video taken from a static camera and is used for various important applications such as video surveill...
Toufiq Parag, Ahmed M. Elgammal, Anurag Mittal
124
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ICCV
2007
IEEE
16 years 5 months ago
Fast Bilinear SfM with Side Information
We study the beneficial effect of side information on the Structure from Motion (SfM) estimation problem. The side information that we consider is measurement of a `reference vect...
Mahesh Ramachandran, Ashok Veeraraghavan, Rama Che...
123
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ECCV
2006
Springer
16 years 5 months ago
Feature Harvesting for Tracking-by-Detection
We propose a fast approach to 3?D object detection and pose estimation that owes its robustness to a training phase during which the target object slowly moves with respect to the ...
Mustafa Özuysal, Vincent Lepetit, Franç...