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» Optimal Parameter Estimation for MRF Stereo Matching
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ECCV
2006
Springer
14 years 7 months ago
Dense Photometric Stereo by Expectation Maximization
Abstract. We formulate a robust method using Expectation Maximization (EM) to address the problem of dense photometric stereo. Previous approaches using Markov Random Fields (MRF) ...
Tai-Pang Wu, Chi-Keung Tang
ICIP
2008
IEEE
14 years 7 months ago
Efficient BP stereo with automatic paramemeter estimation
In this paper, we propose a series of techniques to enhance the computational performance of existing Belief Propagation (BP) based stereo matching that relies on automatic estima...
Shafik Huq, Andreas Koschan, Besma R. Abidi, Mongi...
ECCV
2008
Springer
14 years 7 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
ICIP
2001
IEEE
14 years 6 months ago
Disparity map restoration by integration of confidence in Markov random fields models
This paper proposes some Markov Random Field (MRF) models for restoration of stereo disparity maps. The main aspect is the use of confidence maps provided by the Symmetric Multipl...
Andrea Fusiello, Umberto Castellani, Vittorio Muri...
ICIP
2010
IEEE
13 years 3 months ago
Improving subpixel stereo matching with segment evolution
Segmentation-based approach has shown significant success in stereo matching. By assuming pixels within one image segment belong to the same 3D surface, robust depth estimation ca...
Yao-Jen Chang, Hung-Hsun Liu, Tsuhan Chen