Multimodal complex event detection framework for wide area surveillance

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn , Issue , 2011, Pages 47-54

  Gupta, Himaanshu ^a   Yu, Li ^a   Hakeem, Asaad ^a   Choe, Tae Eun ^a   Haering, Niels ^a   Locasto, Michael ^b  

^a ObjectVideo Inc   (India)

^b UNIVERSITY OF CALGARY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; MONITORING; PROGRAM DEBUGGING; SECURITY SYSTEMS; SENSOR NETWORKS; WIDE AREA NETWORKS;

CAMERA TRACKING; COMPLEX EVENT DETECTION; DATA COLLECTION; EFFECTIVE SYSTEMS; HETEROGENEOUS SENSOR NETWORKS; MARKOV LOGIC NETWORKS; MULTI-MODAL DATA; WIDE AREA SURVEILLANCE;

COMPLEX NETWORKS;

EID: 80054902019     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2011.5981746     Document Type: Conference Paper

References (21)

1. Alchemy open source ai (http://alchemy.cs.washington.edu/).
2. Netwok expect (http://netexpect.org/wiki).
3. Ngsim(next generation simulation): http://ops.fhwa.dot.gov/ trafficanalysistools/ngsim.htm.
4. Scapy (http://www.secdev.org/projects/scapy/).
5. B. Bhanu, C. Ravishankar, A. Roy Chowdhury, H. Aghajan, and D. Terzopoulos. Distributed Video Sensor Networks. Springer, 2011.
6. R. T. Collins, A. J. Lipton, H. Fujiyoshi, and T. Kanade. Algorithms for cooperative multisensor surveillance. In Surveillance, Proceedings of the IEEE, 2001.
7. R. T. Collins, A. J. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, O. Hasegawa, P. Burt, and L. Wixson. A system for video surveillance and monitoring, 2000.
8. J. Earley. An efficient context-free parsing algorithm. Commun. ACM, 26:57-61, January 1983.
9. D. Moore and I. Essa. Recognizing multitasked activities using stochastic context-free grammar. In In Proceedings of AAAI Conference, 2001.
10. R. Nevatia, J. Hobbs, and B. Bolles. An ontology for video event representation. In Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 7 - Volume 07, pages 119-, Washington, DC, USA, 2004. IEEE Computer Society.
11. A. Prati, R. Vezzani, L. Benini, E. Farella, and P. Zappi. An integrated multi-modal sensor network for video surveillance. In Proceedings of the third ACM international workshop on Video surveillance & sensor networks, VSSN '05, pages 95-102, New York, NY, USA, 2005. ACM.
12. Z. Rasheed, X. Cao, K. Shafique, H. Liu, L. Yu, M. Lee, K. Ramnath, T. Choe, O. Javed, and N. Haering. Automated visual analysis in large scale sensor networks. pages 1-10, 2008.
13. M. Richardson and P. Domingos. Markov logic networks. Mach. Learn., 62:107-136, February 2006.
14. R. Rosales and S. Sclaroff. Improved tracking of multiple humans with trajectory prediction and occlusion modeling. In In IEEE CVPR Workshop on the Interpretation of Visual Motion, 1998.
15. M. Shah, O. Javed, and K. Shafique. Automated visual surveillance in realistic scenarios. IEEE MultiMedia, 14:30-39, January 2007.
16. M. Taj and A. Cavallaro. Multi-camera scene analysis using an object-centric continuous distribution hidden markov model. pages IV: 549-552, 2007.
17. G. Taylor, A. Chosak, and P. Brewer. Ovvv: Using virtual worlds to design and evaluate surveillance systems. pages 1-8, 2007.
18. M. Valera and S. A. Velastin. Intelligent distributed surveillance systems: A review. In IEE Proceedings - Vision, Image and Signal Processing, 2005.
19. K. Wang and S. J. Stolfo. Anomalous payload-based network intrusion detection. pages 203-222, 2004.
20. C. Wren, A. Azarbayejani, T. Darrell, and A. Pentland. Pfinder: Real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19:780-785, 1997.
21. B. Wu and R. Nevatia. Detection and tracking of multiple, partially occluded humans by bayesian combination of edgelet based part detectors. Int. J. Comput. Vision, 75:247-266, November 2007.