Measuring the self-consistency of stereo algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1842, Issue , 2000, Pages 282-298

  Leclerc, Yvan G ^a   Luong, Q Tuan ^a   Fua, P ^b  

^a SRI INTERNATIONAL   (United States)

^b EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

STEREO IMAGE PROCESSING;

NEW APPROACHES; POINT CORRESPONDENCE; SELF-CONSISTENCY; STEREO ALGORITHMS;

COMPUTER VISION;

EID: 84944241044     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45054-8_19     Document Type: Conference Paper

References (23)

1. P. Anandan. A computational framework and an algorithm for the measurement of visual motion. IJCV, 2:283-310, 1989.
2. N. Ayache and F. Lustman. Fast and reliable passive trinocular stereovision. In ICCV, pages 422-427, 1987.
3. K. Cho, P. Meer, and J. Cabrera. Performance assessment through bootstrap. PAMI, 19(11):1185-1198, November 1997.
4. G. Csurka, C. Zeller, Z. Zhang, and O. Faugeras. Characterizing the uncertainty of the fundamental matrix. CVGIP-IU, 1996.
5. O. Faugeras, P. Fua, B. Hotz, R. Ma, L. Robert, M. Thonnat, and Z. Zhang. Quantitative and Qualitative Comparison of some Area and Feature-Based Stereo Algorithms. In W. Forstner and S. Ruwiedel, editors, International Workshop on Robust Computer Vision: Quality of Vision Algorithms, pages 1-26, Karlsruhe, Germany, March 1992.
6. W. Forstner. On the geometric precision of digital correlation. In International archives of photogrammetry and remote sensing, volume 24-III, pages 176-189, Helsinki, 1982.
7. P. Fua. Combining Stereo and Monocular Information to Compute Dense Depth Maps that Pres erve Depth Discontinuities. In Int. Joint Conf. on AI, pages 1292-1298, Sydney, Australia, August 1991.
8. P. Fua and Y. G. Leclerc. Object-Centered Surface Reconstruction: Combining Multi-Image Stereo and Shading. IJCV, 16:35-56, 1995.
9. T. Kanade and M. Okutomi. A stereo matching algorithm with an adaptive win-dow: Theory and experiment. PAMI, 16(9):920-932, 1994.
10. Y. Leclerc, Q.-T. Luong, and P. Fua. A framework for detecting changes in terrain. In Proc. Image Understanding Workshop, pages 621-630, Monterey, CA, 1998.
11. Y. Leclerc, Q.-T. Luong, and P. Fua. Self-consistency: a novel approach to charac-terizing the accuracy and reliability of point correspondence algorithms. In Proc. Image Understanding Workshop, pages 793-807, Monterey, CA, 1998.
12. Y. Leclerc, Q.-T. Luong, and P. Fua. Characterizing the performance of multiple-image point-correspondence algorithms using self-consistency. In Proceedings of the Vision Algorithms: Theory and Practice Workshop (ICCV99), Corfu, Greece, September 1999.
13. Y. Leclerc, Q.-T. Luong, and P. Fua. Detecting changes in 3-d shape using self-consistency. In Proc. Conference on Computer Vision and Pattern Recognition, Hilton Head, South Carolina, June 1999.
14. Y. Leclerc, Q.-T. Luong, and P. Fua. Self-consistency: a novel approach to charac-terizing the accuracy and reliability of point correspondence algorithms. In Pro-ceedings of the One-day Workshop on Performance Characterisation and Bench-marking of Vision Systems, Las Palmas de Gran Canaria, Canary Islands, Spain, 1999.
15. L. Matthies. Stereo vision for planetary rovers: Stochastic modeling to near real-time implementation. IJCV, 8(1):71-91, July 1992.
16. R. Mohr, F. Veillon, and L. Quan. Relative 3d reconstruction using multiple uncalibrated images. In CVPR, pages 543-548, NYC, 1993.
17. W. Førstner. Diagnostics and performance evaluation in computer vision. In Per-formance versus Methodology in Computer Vision, NSF/ARPA Workshop, Seattle, WA, 1994.
18. R. Szeliski. Prediction error as a quality metric for motion and stereo. In ICCV99, Corfu, Greece, September 1999.
19. R. Szeliski and S.B. Kang. Recovering 3d shape and motion from image streams using nonlinear least squares. JVCIR, pages 10-28, 1994.
20. R. Szeliski and R. Zabih. An experimental comparison of stereo algorithms. In Proceedings of the Vision Algorithms: Theory and Practice Workshop (ICCV99), Corfu, Greece, September 1999.
21. P.H.S. Torr and A. Zissermann. Performance characterization of fundamental ma-trix estimation under image degradation. mva, 9:321-333, 1997.
22. M. Yachida, Y. Kitamura, and M. Kimachi. Trinocular vision: New approach for correspondence problem. In ICPR, pages 1041-1044, 1986.
23. S. Yi, R.M. Haralick, and L.G. Shapiro. Error propagation in machine vision. MVA, 7:93-114, 1994