Exploiting uncertainty in random sample consensus

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 2074-2081

  Raguram, Rahul ^a   Frahm, Jan Michael ^a   Pollefeys, Marc ^a,b  

^a Brooks Computer Science Building   (United States)

^b ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION PROBLEM; ESTIMATION PROCEDURES; NON-RANDOMNESS; PRIOR INFORMATION; RANDOM SAMPLE CONSENSUS; RANDOMIZED MODELS; ROBUST ESTIMATION; ROBUST ESTIMATION ALGORITHM; SAMPLING PROCESS; SPEED-UPS; THEORETICAL PREDICTION;

ALGORITHMS; COMPUTER VISION;

ESTIMATION;

EID: 77953209549     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459456     Document Type: Conference Paper

References (21)

1. D. Capel. An effective bail-out test for RANSAC consensus scoring. In Proc. BMVC, 2005.
2. O. Chum. Two-view geometry estimation by random sample and consensus. In Ph.D. Dissertation, CTU, 2005.
3. O. Chum and J. Matas. Matching with PROSAC - progressive sample consensus. In Proc. CVPR, 2005.
4. O. Chum and J. Matas. Optimal randomized RANSAC. PAMI, August 2008.
5. O. Chum, J. Matas, and J. Kittler. Locally optimized RANSAC. In Proc. DAGM, 2003.
6. O. Chum, T. Werner, and J. Matas. Two-view geometry estimation unaffected by a dominant plane. In Proc. CVPR, 2005.
7. A. Criminisi, I. Reid, and A. Zisserman. A plane measuring device. In Proc. BMVC, 1999.
8. M. Fisher and R. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. of the ACM, 24(6):381-395, 1981.
9. J.-M. Frahm and M. Pollefeys. RANSAC for (quasi-)degenerate data (QDEGSAC). In Proc. CVPR, 2006.
10. R. M. Haralick. Propagating covariance in computer vision. In In Proc. Workshop on Performance Characteristics of Vision Algorithms, 1994.
11. R. I. Hartley. In defense of the eight-point algorithm. PAMI, 19(6):580-593, 1997.
12. R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. 2000.
13. K. Kanatani. Uncertainty modeling and model selection for geometric inference. PAMI, 26(10):1307-1319, 2004.
14. d,d test. Image and Vision Computing, 22(10):837-842, 2004.
15. C. McGlone, editor. The Manual of Photogrammetry, 5th Ed. The American Society of Photogrammetry, 2004.
16. T. Papadopoulo and M. I. A. Lourakis. Estimating the jacobian of the singular value decomposition: Theory and applications. In Proc. ECCV, 2000.
17. R. Raguram, J.-M. Frahm, and M. Pollefeys. A comparative analysis of RANSAC techniques leading to adaptive realtime random sample consensus. In Proc. ECCV, 2008.
18. P. J. Rousseeuw. Least median of squares regression. Journal of the American Statistical Association, 79:871-890, 1984.
19. C. V. Stewart. MINPRAN: A new robust estimator for computer vision. PAMI, 17(10):925-938, 1995.
20. F. Sur, N. Noury, and M.-O. Berger. Computing the uncertainty of the 8 point algorithm for fundamental matrix estimation. In Proc. BMVC, 2008.
21. P. Torr, A. Zisserman, and S. Maybank. Robust detection of degenerate configurations for the fundamental matrix. Proc. ICCV, 1995.