Representation and recognition of events in surveillance video using petri nets

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2004-January, Issue January, 2004, Pages

  Ghanem, Nagia ^a   DeMenthon, Daniel ^a   Doermann, David ^a   Davis, Larry ^a  

^a University of Maryland ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MONITORING; SECURITY SYSTEMS;

EVENT REPRESENTATIONS; INTERACTIVE SYSTEM; PETRI NET REPRESENTATIONS; PRIMITIVE EVENTS; RECOGNITION ALGORITHM; RECOGNITION METHODS; REPRESENTATION METHOD; SURVEILLANCE APPLICATIONS; SURVEILLANCE VIDEO; USER QUERY;

PETRI NETS;

EID: 84932645954     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2004.430     Document Type: Conference Paper

References (24)

1. J.F. Allen. Maintaining Knowledge about Temporal Intervals. Communications of the ACM, 26(11):832-843, November 1983.
2. D.D. Burdescu and M. Brezovan. High Level Petri Nets and Rule Based Systems for Discrete Event System Modelling. International Journal of Smart Engineering System Design, 3:81-97, 2001.
3. H. Buxton and Shaogang Gong. Visual Surveillance in a Dynamic and Uncertain World. Artificial Intelligence, 78(1-2):431-459, 1995.
4. C. Castel, L. Chaudron, and C. Tessier. What Is Going On? A High Level Interpretation of Sequences of Images. 4th European conference on computer vision, Workshop on conceptual descriptions from images, Cambridge UK, 1996.
5. M. J. Egenhofer and J. Herring. Categorizing Binary Topological Relationships Between Regions, Lines , and Points in Geographic Databases. Technical Report, Department of Surveying Engineering, University of Maine., 1991.
6. A. Elgammal, R. Duraiswami, and L. S. Davis. Efficient Computation of Kernel Density E stimation using Fast Gauss Transform with Applications for Segmentation and Tracking. Second International Workshop on Statistical and Computational Theories of Vision, Vancouver, Canada, 2001.
7. C. L. Forgy RETE: A Fast Algorithm for the Many Pattern/Many Object Pattern Match Problem. Artificial Intelligence 19, 17-37, 1982.
8. S. Hongeng and R. Nevatia. Multi-Agent Event Recognition. ICCV, pages 84-93, 2001.
9. G. S. Hura. Representation and Processing of Rule-Based Expert System Using Petri Nets: A Viable Framework . Proceedings of the 36th Midwest Symposium on Circuits and Systems, 2:934-937, 1993.
10. S. S. Intille and A. F. Bobick. A Framework for Recognizing Multi-Agent Action from Visual Evidence. AAAI/IAAI, pages 518-525, 1999.
11. Y. A. Ivanov and A. F. Bobick. Recognition of Visual Activities and Interactions by Stochastic Parsing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22:852-872, 2000.
12. K. Jensen and G. Rozenbe rg. High-level Petri Nets. Theory and Application. Springer-Verlag, 1991.
13. L. Li. High-level Petri Net Model of Logic Program with Negation . IEEE Transactions on Knowledge and Data Engineering, 6:382-395, 1994.
14. N. Moenne-Loccoz, F. Bremond, and M. Thonnat. Recurrent Bayesian Network for the Recognition of Human Behaviors from Video. ICVS, pages 68-77, 2003.
15. T. Murata and J. Yim. Petri net Methods for Reasoning in Real-Time Control Systems. 1995 IEEE International Symposium on Circuits and Systems, 1:517-520, 1995.
16. T. Murata and D. Zhang. A Predicate-Transition Net Model for Parallel Interpretation of Logic Programs. IEEE Transactions on Software Engineering, 14(4):481-497, 1988.
17. N. Oliver, B. Ro sario, and A. Pentland. A Bayesian Computer Vision System for Modeling Human Interactions. Proceedings of Intl. Conference on Vision Systems ICVS99. Gran Canaria. Spain., January 1999.
18. J. L. Peterson. Petri Net s. ACM Computer Surveys, 9:223-252, 1977.
19. C. S. Pinhanez and A. F. Bobick. Human Action Detection Using PNF Propagation of Temporal Constraints. CVPR, January 1998.
20. P. Remagnino, T. Tan, and K. Baker. Agent Oriented Annotation in Model Based Visual Surveillance. ICCV, 4-7 January 1998,Bombay, India, pages 857-862, January 1998.
21. N. Rota and M. Thonnat. Activity Recognition from Video Sequences using Declarative Models. ECAI 2000, pages 673-680, 2000.
22. T. Starner and A.Pentland. Real-time American Sign Language Recognition from Video Using Hidden Markov Models. Proceedings of International Symposium on Computer Vision, pages 265-270, November 1995.
23. V. Vu, F. Bremond, and M. Thonnat. Automatic Video Interpretation: A Recognition Algorithm for Temporal Scenarios Based on Pre-compiled Scenario Models. ICVS, pages 523-533, 2003.
24. A. K. Zaidi. On Temporal Logic Programming Using Petri Nets. IEEE Transactions on Systems, Man and Cybernetics A, 29(3):245-254, May 1999.