Spectral clustering for robust motion segmentation

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

Volumn 3024, Issue , 2004, Pages 390-401

  Park, Jinhyeong ^a   Zha, Hongyuan ^a   Kasturi, Rangachar ^b  

^a The Pennsylvania State University   (United States)

^b University of South Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTER VISION; FACTORIZATION; IMAGE PROCESSING;

CLUSTERING METHODS; INTERACTION MATRICES; MATRIX FACTORIZATIONS; REAL IMAGE SEQUENCES; ROBUST MOTION; SHAPE SUBSPACE; SPECTRAL CLUSTERING; SUBSPACE SEPARATIONS;

SINGULAR VALUE DECOMPOSITION;

EID: 33745821896     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24673-2_32     Document Type: Article

References (18)

1. C. Tomasi and T. Kanade. Shape and motion from image streams under orthography - a factorization method. International Journal of Computer Vision, 9(2):137-154, 1992.
2. J. Costeira and T. Kanade. A multi-body factorization method for motion analysis. International Journal of Computer Vision, 29(3):159-179, 1998.
3. C. W. Gear. Multibody grouping from motion images. International Journal of Computer Vision, 29(2):133-150, 1998.
4. N. Ichimura. Motion segmentation based on factorization method and discriminant criterion. In Proc. IEEE Int. Conf. Computer Vision, pages 600-605, 1999.
5. Y. Wu, Zhang Z., and J. Y. Huang, T. Lin. Multibody grouping via orthogonal subspace decomposition. In Proc. IEEE Computer Vision and Pattern Recognition, volume 2, pages 252-257, 2001.
6. K. Kanatani. Motion segmentation by subspace separation and model selection. In Proc. IEEE Int. Conf. Computer Vision, volume 2, pages 586-591, 2001.
7. K. Kanatani. Motion segmentation by subspace separation and model selection:model selection and reliability evaluation. Intl. J. of Image and Graphics, 2(2):179-197, 2002.
8. L. Zelnik-Manor and M. Irani. Degeneracies, dependencies and their implications in multi-body and multi-sequence factorizations. In Proc. IEEE Computer Vision and Pattern Recognition, 2003.
9. C. Bregler and H. Hertzmann, A. Biermann. Recovering non-rigid 3d shape from image streams. In Proc. IEEE Computer Vision and Pattern Recognition, 2000.
10. L. Torresani, D. B. Yang, E. J. Alexander, and C. Bregler. Tracking and modeling non-rigid objects with rank constraints. In Proc. IEEE Computer Vision and Pattern Recognition, 2001.
11. M. Brand. Morphable 3d models from video. In Proc. IEEE Computer Vision and Pattern Recognition, 2001.
12. J. Shi and J. Malik. Normalized cut and image segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 22(8):888-905, 2000.
13. M. Gu, H. Zha, C. Ding, X. He, and H. Simon. Spectral relaxation models and structure analysis for k-way graph clustering and bi-clustering. In Technical Report,Department of Computer Science and Engineering, CSE-01-007, 2001.
14. C. Ding, X. He, H. Zha, M. Gu, and H. Simon. Spectral min-max cut for graph partitioning and data clustering. In IEEE International Conference on Data Mining, pages 107-114, 2001.
15. H. Zha, C. Ding, M. Gu, X. He, and H. Simon. Spectral relaxation for k-means clustering. In Neural Information Processing Systems 14, pages 1057-1064, 2002.
16. N. Otsu. A threshold selection method from gray-level histograms. IEEE Trans. on Systems, Man and Cybernetics, SMC-9(1):62-66, 1979.
17. G. H. Golub and C. F. Van Loan. Matrix Computation, 3rd Ed. Johns Hopkins Univ. ress, 2000.
18. K. Kanatani and Y. Sugaya. Multi-stage optimization for multi-body motion segmentation. In Proc. Australia-Japan Advanced Workshop on Computer Vision, pages 25-31, 2003.