A closed form solution to direct motion segmentation

Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

Volumn II, Issue , 2005, Pages 510-515

  Vidal, René ^a   Singaraju, Dheeraj ^a  

^a Johns Hopkins University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; ITERATIVE METHODS; MATHEMATICAL MODELS; OPTIMIZATION; PROBLEM SOLVING; TWO DIMENSIONAL;

IMAGE MEASUREMENTS; MOTION SEGMENTATION; MULTIBODY BRIGHTNESS CONSTANCY CONSTRAINT (MBCC); MULTIPLE MOTION MODELS;

MOTION ESTIMATION;

EID: 24644504900     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2005.19     Document Type: Conference Paper

References (20)

1. S. Ayer and H. Sawhney. Layered representation of motion video using robust maximum-likelihood estimation of mixture models and MDL encoding. In IEEE International Conference on Computer Vision, pages 777-785, 1995.
2. M. Black and P. Anandan. Robust dynamic motion estimation over time. In IEEE Conference on Computer Vision and Pattern Recognition, pages 296-302, 1991.
3. J. Costeira and T. Kanade. A multibody factorization method for independently moving objects. International Journal of Computer Vision, 29(3): 159-179, 1998.
4. T. Darrel and A. Pentland. Robust estimation of a multi-layered motion representation. In IEEE Workshop on Visual Motion, pages 173-178, 1991.
5. R. Hartley and R. Vidal. The multibody trifocal tensor: Motion segmentation from 3 perspective views. In IEEE Conference on Computer Vision and Pattern Recognition, volume I, pages 769-775, 2004.
6. M. Irani and P. Anandan. About direct methods. In Workshop on Vision Algorithms, pages 267-277, 1999.
7. M. Irani, B. Rousso, and S. Peleg. Detecting and tracking multiple moving objects using temporal integration. In European Conference on Computer Vision, pages 282-287, 1992.
8. A. Jepson and M. Black. Mixture models for optical flow computation. In IEEE Conference on Computer Vision and Pattern Recognition, pages 760-761, 1993.
9. Q. Ke and T. Kanade. A robust subspace approach to layer extraction. In IEEE Workshop on Motion and Video Computing, pages 37-43, 2002.
10. M. Shizawa and K. Mase. A unified computational theory for motion transparency and motion boundaries based on eigenenergy analysis. In IEEE Conference on Computer Vision and Pattern Recognition. pages 289-295, 1991.
11. A. Spoerri and S. Ullman. The early detection of motion boundaries. In IEEE International Conference on Computer Vision, pages 209-218, 1987.
12. P. Torr, R. Szeliski, and P. Anandan. An integrated Bayesian approach to layer extraction from image sequences. IEEE Trans. on Pattern Analysis and Machine Intelligence, 23(3):297-303, 2001.
13. P. H. S. Torr. Geometric motion segmentation and model selection. Phil. Trans. Royal Society of London, 356(1740): 1321-1340, 1998.
14. R. Vidal and R. Hartley. Motion segmentation with missing data by PowerFactorization and Generalized PCA. In IEEE Conference on Computer Vision and Pattern Recognition, volume II, pages 310-316, 2004.
15. R. Vidal and Y. Ma. A unified algebraic approach to 2-D and 3-D motion segmentation. In European Conference on Computer Vision, pages 1-15, 2004.
16. R. Vidal, Y. Ma, S. Soatto, and S. Sastry. Two-view multibody structure from motion. International Journal of Computer Vision, 2005.
17. R. Vidal and S. Sastry. Segmentation of dynamic scenes from image intensities. In IEEE Workshop on Motion and Video Computing, pages 44-49, 2002.
18. J. Wang and E. Adelson. Layered representation for motion analysis. In IEEE Conference on Computer Vision and Pattern Recognition, pages 361-366, 1993.
19. Y. Weiss. Smoothness in layers: Motion segmentation using non-parametric mixture estimation. In IEEE Conference on Computer Vision and Pattern Recognition, pages 520-526, 1997.
20. L. Wolf and A. Shashua. Two-body segmentation from two perspective views. In IEEE Conference on Computer Vision and Pattern Recognition, pages 263-270, 2001.