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» Stereo Matching Using Belief Propagation
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ICIAP
2007
ACM
13 years 10 months ago
A New Stereo Algorithm Integrating Luminance, Gradient and Segmentation Informations in a Belief-Propagation Framework
The paper deals with the design and implementation of a stereo algorithm. Disparity map is formulated as a Markov Random Field with a new smoothness constraint depending not only ...
Nello Balossino, Maurizio Lucenteforte, Luca Piova...
ESTIMEDIA
2008
Springer
13 years 10 months ago
Parallelization of belief propagation method on embedded multicore processors for stereo vision
Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation...
Chi-Hua Lai, Kun-Yuan Hsieh, Shang-Hon Lai, Jenq K...
ICCV
2003
IEEE
14 years 10 months ago
Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters
Recent stereo algorithms have achieved impressive results by modelling the disparity image as a Markov Random Field (MRF). An important component of an MRF-based approach is the i...
Marshall F. Tappen, William T. Freeman
CVPR
2005
IEEE
13 years 10 months ago
Dense Photometric Stereo Using Tensorial Belief Propagation
We address the normal reconstruction problem by photometric stereo using a uniform and dense set of photometric images captured at fixed viewpoint. Our method is robust to spurio...
Kam-Lun Tang, Chi-Keung Tang, Tien-Tsin Wong
ICMCS
2010
IEEE
354views Multimedia» more  ICMCS 2010»
13 years 9 months ago
High-quality multi-view depth generation using multiple color and depth cameras
In this paper, we propose a high-quality multi-view depth generation method using multiple color and depth cameras. After we capture low-resolution depth maps by three TOF cameras...
Yun-Suk Kang, Yo-Sung Ho