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» An Attentional Framework for Stereo Vision
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CVPR
2008
IEEE
15 years 12 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
CVPR
2005
IEEE
15 years 3 months ago
Symmetric Stereo Matching for Occlusion Handling
In this paper, we propose a symmetric stereo model to handle occlusion in dense two-frame stereo. Our occlusion reasoning is directly based on the visibility constraint that is mo...
Jian Sun, Yin Li, Sing Bing Kang
ICCV
2007
IEEE
15 years 11 months ago
Variational Stereo Vision with Sharp Discontinuities and Occlusion Handling
This paper addresses the problem of correspondence establishment in binocular stereo vision. We suggest a novel variational approach that considers both the discontinuities and oc...
Rami Ben-Ari, Nir A. Sochen
CVPR
2004
IEEE
15 years 12 months ago
Efficient Belief Propagation for Early Vision
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher
ICPR
2008
IEEE
15 years 4 months ago
Adaptive semantic Bayesian framework for image attention
Image attention is the basic technique for many computer vision applications. In this paper, we propose an adaptive Bayesian framework to detect the image attention in color image...
Wei Zhang, Q. M. Jonathan Wu, Guanghui Wang