Inferring social roles in long timespan video sequence

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 1456-1463

  Zhang, Jiangen ^a,c   Hu, Wenze ^b   Yao, Benjamin ^b   Wang, Yongtian ^a   Zhu, Song Chun ^b,c  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c Lotus Hill Research Institute   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ATOMIC ACTIONS; BAYESIAN INFERENCE; COMPOSITION RULE; DAILY ACTIVITY; HIGH PRECISION; HOTSPOTS; PROBABILISTIC OUTPUT; SURVEILLANCE CAMERAS; SURVEILLANCE VIDEO; VIDEO SEQUENCES;

BAYESIAN NETWORKS; FORMAL LANGUAGES; IMAGE PROCESSING; INFERENCE ENGINES; MANAGERS; MONITORING; SEMANTICS; VIDEO RECORDING;

SECURITY SYSTEMS;

EID: 84863074227     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130422     Document Type: Conference Paper

References (16)

1. M. Al-Hames and G. Rigoll. A multi-modal mixed-state dynamic bayesian network for robust meeting event recognition from disturbed data. IEEE ICME, 2005.
2. M. Brand, N. Oliver, and A. Pentland. Coupled hidden markov models for complex action recognition. CVPR, 1997.
3. L.-B. Chang, Y. Jin, W. Zhang, and E. B. S. Geman. Context, computation, and optimal roc performance in hierarchical models. IJCV, 2010.
4. R. Dechter and R. Mateescu. AND/OR search spaces for graphical models. Artificial Intelligence, 171(2-3):73-106, 2007.
5. L. Ding and A. Yilmaz. Learning relations among movie characters: a social network perspective. In ECCV, 2010.
6. J. K. Hamlin, K. Wynn, and P. Bloom. Social evaluation by preverbal infants. Nature, 450(7169):557-559, Nov. 2007.
7. J. C. Earley. An Efficient Context-Free Parsing Algorithm. PhD thesis, Carnegie-Mellon Univ, 1968.
8. M. S. Ryoo and J. K. Aggarwal. Recognition of composite human activities through context-free grammar based representation. CVPR, pages 1709-1718, 2006.
9. P. Natarajan and R. Nevatia. Coupled hidden semi markov models for activity recognition. IEEE Workshop on Motion and Video Computing, 2007.
10. J. Pearl. Heuristics: intelligent search strategies for computer problem solving. Addison-Wesley Long-man Publishing Co., Inc, Boston, MA, 1984.
11. M. Pei, Y. Jia, and S.-C. Zhu. Parsing video events with goal inference and intent prediction. 2011.
12. A. Stolcke. An efficient probabilistic context-free parsing algorithm that computes prefix probabilities. Computational Linguistics, 1995.
13. T. D. Ullman, C. L. Baker, M. Owen, E. Owain, N. D. Goodman, and J. B. Tenenbaum. Help or hinder : Bayesian models of social goal inference. NIPS, 2009.
14. T. Yu, S.-N. Lim, K. Patwardhan, and N. Krahnstoever. Monitoring, recognizing and discovering social networks. CVPR, 2009.
15. Z. Zhang, T. Tan, and K. Huang. An extended grammar system for learning and recognizing complex visual events. PAMI, 2011.
16. S.-C. Zhu and D. Mumford. A stochastic grammar of images. Foundat. Trends Comput graphics Vision, 2:259-362, 2007.