Robust unambiguous parametrization of the essential manifold

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Subbarao, Raghav ^a,b   Genc, Yakup ^b   Meer, Peter ^a  

^a RUTGERS UNIVERSITY   (United States)

^b SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CAMERAS; COMPUTER VISION; ELECTRIC NETWORK ANALYSIS; ESTIMATION; FEATURE EXTRACTION; IMAGE PROCESSING; PATTERN RECOGNITION;

CALIBRATED CAMERAS; EPIPOLAR CONSTRAINTS; ESSENTIAL MATRICES; GENERAL MOTION MODEL; PARAMETRIZATION; REAL DATA SETS; ROBUST ESTIMATIONS; SYNTHETIC DATA; THEORETICAL ANALYSIS;

MATRIX ALGEBRA;

EID: 51949083780     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587689     Document Type: Conference Paper

References (22)

1. E. Begelfor and M. Werman. How to put probabilities on homographies. IEEE Trans. PAMI, 27(10):1666-1670, 2005.
2. W. M. Boothby. An Introduction to Differentiable Manifolds and Riemannian Geometry. Academic Press, 2002.
3. D. Comaniciu and P. Meer. Mean shift: A robust approach toward feature space analysis. IEEE Trans. PAMI, 24:603-619, May 2002.
4. A. Edelman, T. A. Arias, and S. T. Smith. The geometry of algorithms with orthogonality constraints. SIAM Journal on Matrix Analysis and Applications, 20(2):303-353, 1998.
5. R. Ferreira and J. Xavier. Hessian of the Riemannian squared-distance function on connected locally symmetric spaces with applications. In Controlo 2006, 7th Portuguese Conference on Automatic Control, 2006.
6. C. Geyer, R. Bajcsy, and S. Sastry. Euclid meets Fourier: Applying harmonic analysis to essential matrix estimation in omnidirectional cameras. In Proc.of Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras, 2004.
7. V. M. Govindu. Lie-algebraic averaging for globally consistent motion estimation. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Washington, DC, volume I, pages 684-691, 2004.
8. R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, 2000.
9. U. Helmke, K. Huper, P. Lee, and J. Moore. Essential matrix estimation using Gauss-Newton iterations on a manifold. International J. of Computer Vision, 2007.
10. K. Kanatani. Group Theoretical Methods in Image Understanding. Springer-Verlag, 1990.
11. J. Kosecka, Y. Ma, and S. Sastry. Optimization criteria, sensitivity and robustness. In B. Triggs, A. Zisserman, and R. Szelisky, editors, Vision Algorithms: Theory and Practice, pages 168-182. Springer, 2000.
12. H. Longuet-Higgins. A computer algorithm for reconstructing a scene from two projections. Nature, 293:133-135, 1981.
13. D. G. Lowe. Distinctive image features from scale-invariant keypoints. International J. of Computer Vision, 60(2):91-110, 2004.
14. Y. Ma, J. Kosecka, and S. Sastry. Optimization criteria and geometric algorithms for motion and structure estimation. International J. of Computer Vision, 44(3):219-249, 2001.
15. S. J. Maybank. Theory of Reconstruction from Image Motion. Springer-Verlag, 1992.
16. D. Nister. An efficient solution to the five-point relative pose problem. IEEE Trans. PAMI, 26(6):756-770, 2004.
17. W. Rossmann. Lie Groups: An Introduction through Linear Groups. Oxford University Press, 2003.
18. S. Soatto, R. Frezza, and P. Perona. Recursive motion estimation on the essential manifold. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, San Francisco, CA, pages 428-433, 1993.
19. S. Soatto, P. Perona, R. Frezza, and G. Picci. Motion estimation via dynamic vision. In Proc. European Conf. on Computer Vision, Stockholm, Sweden, volume II, pages 61-72, 1994.
20. R. Subbarao, Y. Genc, and P. Meer. Nonlinear mean shift for robust pose estimation. In 8th IEEE Workshop on Applications of Computer Vision, Austin, TX, February 2007.
21. R. Subbarao and P. Meer. Nonlinear mean shift for clustering over analytic manifolds. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, New York, NY, volume I, pages 1168-1175, 2006.
22. O. Tuzel, R. Subbarao, and P. Meer. Simultaneous multiple 3D motion estimation via mode finding on Lie groups. In Proc. 10th Intl. Conf. on Computer Vision, Beijing, China, volume 1, pages 18-25, 2005.