Simple but effective tree structures for dynamic programming-based stereo matching

VISAPP 2008 - 3rd International Conference on Computer Vision Theory and Applications, Proceedings

Volumn 2, Issue , 2008, Pages 415-422

  Bleyer, Michael ^a   Gelautz, Margrit ^a  

^a VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

Fast stereo method; Stereo matching; Tree based dynamic programming

Indexed keywords

ARTS COMPUTING; COMPUTER VISION; DYNAMIC POSITIONING; DYNAMIC PROGRAMMING; EDGE DETECTION; GRAPH THEORY; IMAGE MATCHING; IMAGE PROCESSING; IMAGE SEGMENTATION; PERCOLATION (SOLID STATE); PIXELS; PROGRAMMING THEORY; SYSTEMS ENGINEERING;

COMPETING ALGORITHMS; COMPUTATION PROCESS; DISPARITY MAPS; ENERGY FUNCTIONS; FAST METHODS; FAST STEREO METHOD; IMAGE PIXELS; OPTIMAL COSTS; REFERENCE FRAMES; SCANLINE; STEREO CORRESPONDENCES; STEREO MATCHING; STEREO PAIRS; TEST SETS; TREE GRAPHS; TREE STRUCTURES; TREE-BASED DYNAMIC PROGRAMMING;

TREES (MATHEMATICS);

EID: 57549092581     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Birchfield, S. and Tomasi, C. (1998). A pixel dissimilarity measure that is insensitive to image sampling. TPAMI, 20(4):401-406.
2. Bleyer, M. and Gelautz, M. (2005). A layered stereo matching algorithm using image segmentation and global visibility constraints. ISPRS Journal, 59(3): 128-150.
3. Bobick, A. and Intille, S. (1999). Large occlusion stereo. IJCV,33(3):181-200.
4. Boykov, Y., Veksler, O., and Zabih, R. (2001). Fast approximate energy minimization via graph cuts. TPAMI, 23(11): 1222-1239.
5. Deng, Y. and Lin, X. (2006). A fast line segment based dense stereo algorithm using tree dynamic programming. In ECCV, volume 3, pages 201-212.
6. Gong, M. and Yang, Y. (2005). Near real-time reliable stereo matching using programmable graphics hardware. In CVPR, pages 924-931.
7. Hirschmuller, H. (2005). Accurate and efficient stereo processing by semi-global matching and mutual information. In CVPR, volume 2, pages 807-814.
8. HirschmÜller, H. (2006). Stereo vision in structured environments by consistent semi-global matching. In CVPR, volume 2, pages 2386-2393.
9. Kim, J., Lee, K., Choi, B., and Lee, S. (2005). A dense stereo matching using two-pass dynamic programming with generalized ground control points. In CVPR, volume 2, pages 1075-1082.
10. Lei, C, Selzer, J., and Yang, Y. (2006). Region-tree based stereo using dynamic programming optimization. In CVPR, volume 2, pages 2378-2385.
11. Ogale, A. S. and Aloimonos, Y. (2004). Stereo correspondence with slanted surfaces: critical implications of horizontal slant. In CVPR, pages 568-573.
12. Ohta, Y. and Kanade, T. (1985). Stereo by intra- and interscanline search. TPAMI, 7(2): 139-154.
13. Scharstein, D. and Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV, 47(1/2/3):7-42. http://www.middlebury.edu/stereo/.
14. Sun, J., Zheng, N., and Shum, H. (2003). Stereo matching using belief propagation. TPAMI, 25(7):787-800.
15. Veksler, O. (2005). Stereo correspondence by dynamic programming on a tree. In CVPR, pages 384-390.
16. Wang, L., Liao, M., Gong, M., Yang, R., and Nister, D. (2006). High quality real-time stereo using adaptive cost aggregation and dynamic programming. In 3DPVT.