Three-step image rectification

British Machine Vision Conference, BMVC 2010 - Proceedings

Volumn , Issue , 2010, Pages

  Monasse, Pascal ^a   Morel, Jean Michel ^b   Tang, Zhongwei ^b  

^a UNIVERSITÉ PARIS EST   (France)

^b Paris Descartes University   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CAMERAS; COMPUTER VISION; OPTIMIZATION;

CAMERA ROTATIONS; COMPARATIVE EXPERIMENTS; DENSE STEREO MATCHING; DISTORTION FUNCTIONS; EMPIRICAL MEASURE; IMAGE RECTIFICATION; MINIMIZATION ALGORITHMS; UN-CALIBRATED CAMERA;

IMAGE MATCHING;

EID: 84898418934     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.24.89     Document Type: Conference Paper

References (17)

1. N. Ayache and C. Hansen. Rectification of images for binocular and trinocular stereovision. ICPR, 1988.
2. M.A. Fischler and R.C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. CACM, 24(3):381-395, 1981.
3. Jan-Michael Frahm and Marc Pollefeys. Ransac for (quasi-)degenerate data (qdegsac). CVPR, 1, 2006.
4. A. Fusiello and L. Irsara. Quasi-Euclidean uncalibrated epipolar rectification. ICPR, 2008.
5. A. Fusiello, E. Trucco, and A. Verri. A compact algorithm for rectification of stereo pairs. Machine Vision and Applications, 12(1):16-22, 2000.
6. J. Gluckman and S.K. Nayar. Rectifying transformations that minimize resampling effects. CVPR, 1:111, 2001.
7. R.I. Hartley. In defense of the eight-point algorithm. IEEE TPAMI Intelligence, 19(6):, 1997.
8. R.I. Hartley. Theory and practice of projective rectification. IJCV, 35(2):115-127, 1999.
9. R.I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, ISBN: 0521540518, second edition, 2004.
10. C. Loop and Z. Zhang. Computing rectifying homographies for stereo vision. CVPR, 1:, 1999.
11. David G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):, 2004.
12. J. Mallon and Paul F. Whelan. Projective rectification from the fundamental matrix. Image and Vision Computing, 23:643-650, 2005.
13. L. Moisan and B. Stival. A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix. IJCV, 57(3):201-218, 2004.
14. Daniel Oram. Rectification for any epipolar geometry. BMVC, 2001.
15. T. Papadopoulo and M.I.A. Lourakis. Estimating the jacobian of the singular value decomposition: theory and application. ECCV, 1:554-570, 2000.
16. Koch R. Pollefeys M. and Van Gool L. A simple and efficient rectification method for general motion. ICCV, 1:496-501, 1999.
17. W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery. Numerical Recipes. The Art of Scientific Computing. Third Edition. Cambridge University Press, 2007.