Stereo matching via learning multiple experts behaviors

BMVC 2006 - Proceedings of the British Machine Vision Conference 2006

Volumn , Issue , 2006, Pages 97-106

  Kong, Dan ^a   Tao, Hai ^a  

^a University of California Santa Cruz   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION; ITERATIVE METHODS;

DEPTH DISCONTINUITIES; DEPTH ESTIMATION; HISTOGRAM-BASED METHOD; LEARNING-BASED ALGORITHMS; MATCHING BEHAVIOR; METROPOLIS-HASTINGS ALGORITHM; NORMALIZED CROSS-CORRELATION (NCC); STATE-OF-THE-ART METHODS;

IMAGE MATCHING;

EID: 79952507216     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. http://www.middlebury.edu/stereo.
2. P. N. Belhumeur. A bayesian-approach to binocular stereopsis. IJCV, 19(3):237-260, August 1996.
3. Y Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. PAMI, 23(11):1222-1239, 2001.
4. I. J. Cox, S. L. Hingorani, S. B. Rao, and B. M. Maggs. A maximum-likelihood stereo algorithm. CVIU, 63(3):542-567, 1996.
5. T. Kanade and M. Okutomi. A stereo matching algorithm with an adaptive window: theory and experiment. PAMI, 16(9):920-932, September 1994.
6. S. Roth and M. J. Black. On the spatial statistics of optical flow. In ICCV 05, pages 42-49, 2005.
7. D. Scharstein and R. Szeliski. Stereo matching with nonlinear diffusion. IJCV, 28(2):155-174, July 1998.
8. D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV, 47(1):7-42, 2002.
9. J. Sun, H. Y. Shum, and N. N. Zheng. Stereo matching using belief propagation. In ECCV02, pages II: 510-524, 2002.
10. O. Veksler. Fast variable window for stereo correspondence using integral images. In CVPR03, pages I: 556-561, 2003.
11. K. J. Yoon and I. S. Kweon. Locally adaptive support-weight approach for visual correspondence search. In CVPR05, pages II: 924-931, 2005.