Real-time global stereo matching using hierarchical belief propagation

BMVC 2006 - Proceedings of the British Machine Vision Conference 2006

Volumn , Issue , 2006, Pages 989-998

  Yang, Qingxiong ^a   Wang, Liang ^a   Yang, Ruigang ^a   Wang, Shengnan ^b   Liao, Miao ^a   Nistér, David ^a  

^a UNIVERSITY OF KENTUCKY   (United States)

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION;

BELIEF PROPAGATION; GLOBAL ALGORITHMS; GRAPHICS HARDWARE; HIERARCHICAL BELIEF PROPAGATION; NUMBER OF ITERATIONS; PERFORMANCE GAIN; REAL TIME PERFORMANCE; STEREO MATCHING;

BACKPROPAGATION;

EID: 84898032886     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Q. Yáng, L. Wang, R. Yang, H. Stewénius. and D. Nistér, Stereo matching with color-weighted correlation, hierarchical belief propagation and occlusion handling, CVPR, June 2006.
2. M. Bleyer and M. Gelautz, A Layered Stereo Algorithm Using Image Segmentation and Global Visibility Constraints, ICIP, pp. 2997-3000, 2004.
3. S. Birchfield and C. Tomasi, A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling, PAMI, Vol. 20, No. 4, April 1998.
4. Y. Boykov, O. Veksler and R. Zabih, Fast Approximate Energy Minimization via Graph Cuts, PAMI, Vol. 23, No. 11, 2001.
5. P. F. Felzenszwalb and D. P. Huttenlocher, Efficient Belief Propagation for Early Vision, CVPR, Vol. I:261-268, 2004.
6. V. Kolmogorov and R. Zabih, Computing Visual Correspondence with Occlusions using Graph Cuts, ICCV, Vol. I:508-515 2001.
7. D. Scharstein and R. Szeliski, Middlebury Stereo Vision Research Page, http://bj.middlebury.edu/~schar/stereo/newEval/php/results.php
8. J. Sun, N.-N. Zheng and H.-Y. Shum, Stereo Matching Using Belief Propagation, PAMI, Vol. 25, No. 7, July 2003.
9. V. Kolmogorov and R. Zabih, Multi-camera scene reconstruction via graph cuts, ECCV, Vol. III:82-96, 2002.
10. D. Scharstein and R. Szeliski, A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms, IJCV, 47(1):7-42, May 2002.
11. J. Sun, Y. Li, S. B. Kang and H.-Y. Shum, Symmetric Stereo Matching for Occlusion Handling, CVPR, Vol. II:399-406, 2005.
12. L. Wang, M. Liao, M. Gong, R. Yang, and D. Nistér, High-quality real-time stereo using adaptive cost aggregation and dynamic programming, 3DPVT 2006.
13. M. Gong and Y. Yang, Near real-time reliable stereo matching using programmable graphics hardware, CVPR, Vol I:924-931, 2005.
14. S. Forstmann, J. Ohya, Y. Kanou, A. Schmitt, and S. Thuering, Real-time stereo by using dynamic programming, CVPR, Workshop on real-time 3D sensors and their use, 2004.
15. C. Sun, Fast stereo matching using rectangular subregioning and 3D maximum-surface techniques, CVPR, Stereo workshop, 2001.
16. H. Hirschmüller, Improvements in real-time correlation-based stereo vision, CVPR, Stereo workshop, 2001.
17. H. Hirschmüller, P. R. Innocent, and J. M. Garibaldi. Real-time correlation-based stereo vision with reduced border errors, IJCV, 47(1/2/3):229-246, April-June 2002.
18. O. Veksler. Fast variable window for stereo correspondence using integral images, CVPR, Vol I: 556-561, 2003.
19. Yuichi Ohta, Takeo Kanade, Stereo by intea nad inter-scanline search using dynamic programming, PAMI, 1985.
20. J. Kim, K.M. Lee, B.T. Choi, and S.U. Lee. A dense stereo matching using two-pass dynamic programming with generalized ground control points, IEEE CVPR, Vol II: 1075-1082, 2005.
21. O. Veksler. Stereo correspondence by dynamic programming on a tree, IEEE CVPR, Vol II: 384-390, 2005.