Tensor space learning for analyzing activity patterns from video sequences

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2007, Pages 63-68

  Wang, Liang ^a   Leckie, Christopher ^a   Wang, Xiaozhe ^a   Kotagiri, Ramamohanarao ^a   Bezdek, Jim ^b  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b UNIVERSITY OF WEST FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVITY PATTERNS; HAUSDORFF DISTANCE; HUMAN ACTIVITIES; INTERNATIONAL CONFERENCES; MOTION TRAJECTORIES; SPATIAL SCALING; SUB SPACES; TEMPORAL ORDER; VIDEO DATA; VIDEO SEQUENCING;

ADMINISTRATIVE DATA PROCESSING; DATA MINING; DECISION SUPPORT SYSTEMS; FORESTRY; IMAGING TECHNIQUES; INFORMATION MANAGEMENT; MINING; MOTION ESTIMATION; PHOTOGRAPHY; SEARCH ENGINES; TENSORS; TRAJECTORIES; VIDEO RECORDING;

KNOWLEDGE BASED SYSTEMS;

EID: 49549095746     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2007.70     Document Type: Conference Paper

References (21)

1. J. Aggarwal and Q. Cai. Human motion analysis: A review. Computer Vision and Image Understanding, 73(3):428-440, 1999.
2. P. Belhumeur, J. Hepanha, and D. Kriegman. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE PAMI, 19(7):711-720, 1997.
3. M. Belkin and P. Niyogi. Laplacian eigenmaps and spectral techniques for embedding and clustering. In NIPS, volume 14, 2001.
4. J. Ben-Arie, Z. Wang, P. Pandit, and S. Rajaram. Human activity recognition using multidimensional indexing. IEEE PAMI, 24(8):1091-1104, 2002.
5. J. C. Bezdek and R. J. Hathaway. VAT: A tool for visual assement of (cluster) tendency. In Proc. International Joint Conference on Neural Networks, pages 2225-2230, 2002.
6. M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Basri. Actions as space-time shapes. In Proc. International Conference on Computer Vision, pages 1395-1402, 2005.
7. A. Bobick and J. Davis. The recognition of human movement using temporal templates. IEEE PAMI, 23(3):257-267, 2001.
8. S. Chen, M. Shyu, C. Zhang, and J. Strickrott. Multimedia data mining for traffic video sequences. In Proc. International Workshop on Multimedia Data Mining (MDM/KDD), pages 78-86, 2001.
9. A. Efros, A. Berg, G. Mori, and J. Malik. Recognizing action at a distance. In Proc. International Conference on Computer Vision, 2003.
10. X. He, D. Cai, and P. Niyogi. Tensor subspace analysis. In NIPS, volume 18, 2005.
11. X. He and P. Niyogi. Locality preserving projections. In NIPS, volume 16, 2003.
12. L.Wang, W.M.Hu, and T.N.Tan. Recent developments in human motion analysis. Pattern Recognition, 36(3):585-601, 2003.
13. A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: analysis and an algorithm. In NIPS, volume 14, 2001.
14. A. Rosenfeld, D.Doermann, and D. DeMenthon. Video Mining. Kluwer, 2003.
15. S. Roweis and L. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(12), 2000.
16. C. Schuldt, I. Laptev, and B. Caputo. Recognizing human actions: A local SVM approach. In Proc. International Conference on Pattern Recognition, pages 32-36, 2004.
17. M. D. Shapiro and M. B. Blaschko. Stability of Hausdorff-based distance measures. In Proc. IASTED Conference on Visualization, Imaging and Image Processing, 2004.
18. M. Vasilescu and D. Terzopoulos. Multilinear subspace analysis for image ensembles. In Proc. International Conference on Computer Vision and Pattern Recognition, 2003.
19. A. Veeraraghavan, R. Chellappa, and A. Roy-Chowdhury. The function space of an activity. In Proc. Inte. Conference on Computer Vision and Pattern Recognition, 2006.
20. U. von Luxburg. A tutorial on spectral clustering. Technical report, Max Planck Institute, 2006.
21. L. Zelnik-Manor and P. Perona. Self-tuning spectral clustering. In NIPS, volume 16, 2004.