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CVPR
2009
IEEE
16 years 6 months ago
Alphabet SOUP: A Framework for Approximate Energy Minimization
Many problems in computer vision can be modeled using conditional Markov random fields (CRF). Since finding the maximum a posteriori (MAP) solution in such models is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
ICCV
2009
IEEE
1957views Computer Vision» more  ICCV 2009»
16 years 3 months ago
Robust Visual Tracking using L1 Minimization
In this paper we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, corru...
Xue Mei, Haibin Ling
88
Voted
CVPR
1999
IEEE
16 years 26 days ago
Integrating Shape from Shading and Range Data Using Neural Networks
This paper presents a framework for integrating multiple sensory data, sparse range data and dense depth maps from shape from shading in order to improve the 3D reconstruction of ...
Mostafa G.-H. Mostafa, Sameh M. Yamany, Aly A. Far...
101
Voted
CVPR
2004
IEEE
16 years 26 days ago
Motion Estimation by Swendsen-Wang Cuts
Our paper has two main contributions. Firstly, it presents a model for image sequences motivated by an image encoding perspective. It models accreted regions, where objects appear...
Adrian Barbu, Alan L. Yuille
100
Voted
CVPR
2004
IEEE
16 years 26 days ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...