Quasi-Periodic Event Analysis for Social Game Retrieval

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 112-119

  Wang, Ping ^a   Abowd, Gregory D ^a   Rehg, James M ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EVENT ANALYSIS; HOME MOVIES; MOTION PATTERN; PROPERTY; QUASI-PERIODIC; QUASI-PERIODIC MOTION; SOCIAL GAMES; SOCIAL INTERACTIONS; VIDEO-CLIPS; YOUTUBE;

COMPUTERS;

EID: 85026939101     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459151     Document Type: Conference Paper

References (26)

1. M. Brand, N. Oliver, and A. Pentland. Coupled hidden markov models for complex action recognition. In CVPR, 1997.
2. P. Buehler, M. Everingham, and A. Zisserman. Learning sign language by watching tv (using weakly aligned subtitles). In CVPR, 2009.
3. R. Cutler and L. S. Davis. Robust real-time periodic motion detection, analysis, and applications. IEEE T-PAMI, 22(8):781-796, 2000.
4. P. Dollér, V. Rabaud, G. Cottrell, and S. Belongie. Behavior recognition via sparse spatio-temporal features. In IEEE Workshop on VS-PETS, pages 65-72, 2005.
5. Q. Fan, R. Bobbitt, Y. Zhai, A. Yanagawa, S. Pankanti, and A. Hampapur. Recognition of repetitive sequential human activity. In CVPR, 2009.
6. J. Hoey and J. J. Little. Value-directed human behavior analysis from video using partially observable markov decision processes. IEEE T-PAMI, 29(7):1118-1132, 2007.
7. H. Jhuang, T. Serre, L. Wolf, and T. Poggio. A biologically inspired system for action recognition. In ICCV, 2007.
8. Y. Ke, R. Sukthankar, and M. Hebert. Event detection in crowded videos. In ICCV, 2007.
9. I. Laptev. On space-time interest points. IJCV, 64(2/3):107-123, 2005.
10. I. Laptev, S. J. Belongie, P. Perez, and J. Wills. Periodic motion detection and segmentation via approximate sequence alignment. In ICCV, pages 816-823, 2005.
11. I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld. Learning realistic human actions from movies. In CVPR, 2008.
12. J. Liu, J. Luo, and M. Shah. Recognizing realistic actions from videos “in the wild”. In CVPR, 2009.
13. E. McCreight. A space-economical suffix tree construction algorithm. Journal of the ACM, 23:262-272, 1976.
14. C. Needham, P. Santos, D. Magee, V. Devin, D. Hogg, and A. Cohn. Protocols from perceptual observations. Artificial Intelligence, 167(1-2):103-136, 2005.
15. J. C. Niebles, H. Wang, and L. Fei-Fei. Unsupervised learning of human action categories using spatial-temporal words. In BMVC, 2006.
16. S. Nowozin, G. Bakir, and K. Tsuda. Discriminative subsequence mining for action classification. In ICCV, 2007.
17. R. Polana and R. Nelson. Detection and recognition of periodic, non-rigid motion. IJCV, 23(3):261-282, 1997.
18. C. Schuldt, I. Laptev, and B. Caputo. Recognizing human actions: A local SVM approach. In ICPR, 2004.
19. E. Shechtman and M. Irani. Matching local self-similarities across image and videos. In CVPR, 2007.
20. T. Starner, J. Weaver, and A. Pentland. Real-time American sign language recognition using desk and wearable computer-based video. IEEE T-PAMI, 20(12):1371-1375, 1998.
21. A. Wilson, A. Bobick, and J. Cassell. Recovering the temporal structure of natural gesture. In AFGR, 1996.
22. A. D. Wilson and A. F. Bobick. Parametric hidden markov models for gesture recognition. IEEE T-PAMI, 21(9):884-900, 1999.
23. S.-F. Wong, T.-K. Kim, and R. Cipolla. Learning motion categories using both semantic and structural information. In CVPR, 2007.
24. Y. Yacoob and M. Black. Parameterized modeling and recognition of activities. CVIU, (2):232-247, 1999.
25. J. Yang, W. Wang, and P. S. Yu. Infominer: mining surprising periodic patterns. In SIGKDD, pages 395-400, 2001.
26. H. Zhong, J. Shi, and M. Visontai. Detecting unusual activity in video. In CVPR, 2004.