Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805
The refinement of the term «event» was held, identification of the properties that characterizes event was conducted. The analysis of approaches to the problem of developing the event model was conducted. The justification of choosing the base model for event analysis problem was held.

1. Hu W.,Tan T., Wang L. and others. A Survey on Visual Surveillance of Object Motion and Behaviors, Systems, Man and Cybernetics, Part C., 2004, No 4, pp.334-352 (In English), doi: 10.1109/TSMCC.2004.829274, url: dfiles/yzchen/200812041421/A%20Survey%20on%20Visual%20Surveillance%20of%20Object%20Motion%20and%20Behaviors.pdf.

2. Aggarwal J.K., and Cai Q. Human Motion Analysis: A Review, Computer Vision and Image Undestanding,1999, No 3, pp. 428 -440 (In English), doi:10.1006/cviu.1998.0744, url: /Publications/Q.%20Cai,%20Human%20Motio n%20Analysis%20A%20Review.pdf.

3. Cohn A.G., Magee D.R., Galata A. and others. Towards an Architecture for Cognitive Vision Using Spatio-Temporal Representations and Abduction, In Spatial Cognition,2003, No 2, pp. 232-248 (In English), doi:

4. Hongenhg S. and Nevatia R. Multi-Agent Event Recognition, International Conference on Computer Vision, 2001, pp. 84- 93 (In English), doi: 10.1109/ICCV.2001.937608,url: /file/2013020222243062401.pdf.

5. Buxton H. Generative Midels for Learning and Understanding Dynamic Scene Activity, ECCV Workshop on Generative Model Based Vision, 2002, pp. 154-169 (In English), doi: =, url: /dir_e/cognition/eccv02.pdf.

6. Medioni G.G., Cohen I., Bremond F. and others. Event Detection and Analysis from Video Streams, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, No 8, pp. 873-889 (In English), doi: 10.1109/34.946990, url: /iuw-event98.pdf.                       

7. Howarth R.J. and Buxton H. Conceptual Descriptions from Monitoring and Watching Image Sequences, Image and Vision Computting,2000, No 18, pp. 105-135 (In English),url: article/pii/S0262885699000256.http://dx.doi. org/10.1016/S0262-8856(99)00025-6.

8. Bobick A.F. Movement, Activity and Action: The Role of Knowledge in the Perception of Motion, Royal Society Workshop on Knowledge-based Vision in Man and Machine, 1997, No 6, pp. 1257-1265 (In English), doi: 10.1098/rstb.1997.0108, url: cles/PMC1692010/pdf/9304692.pdf.

9. Ng A.Y. and Jordan M.I. On Discriminative vs. Generative Classifiers: A Comparison of Logistic Regression and Naive Bayes, Neural Information Processing Systems, 2001, No 1, pp. 841-848 (In English), doi: 10.1007/s11063-008-9088-7 url: s01-discriminativegenerative.pdf.

10. Ulusoy I. and Bishop C.M. Generative Versus Discriminative Methods for Object Recognition, Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, No 2, pp. 258-265 (In English), doi: 10.1007/11957959_9, url: /CVPR/2005/DATA/14-4P_26.PDF.

11. Ghanem N., DeMenthon D., Doermann D. and others. Representation and Recognition of Events in Surveillance Video Using Petri Nets, Computer Vision and Pattern Recognition Workshop, 2004, No 1, pp. 112- 132 (In English), doi: 10.1109/CVPR.2004.156, url: /Papers/nghanem-04/nghanem-04.pdf.

12. Kovalenko N.V. and Godovichenko N.A. The Model of Video Semantic Analysis System for Objects of Interest Deviant Behavior Detection [Model' sistemy semanticheskogo analiza videopotoka dlya vyyavleniya deviantnogo povedeniya ob"ektov interesa], Iskusstvennyi intellect, 2012, No 4, pp. 124-132 (In Russian).

Last download:
2017-11-16 10:41:05

[ © KarelWintersky ] [ All articles ] [ All authors ]
[ © Odessa National Polytechnic University, 2014. Any use of information from the site is possible only under the condition that the source link! ]