Detection of inconsistent regions in video streams

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5292, Issue , 2004, Pages 202-210

  Gaborski, Roger S ^a   Vaingankar, Vishal S ^a   Chaoji, Vineet S ^a   Teredesai, Ankur M ^a   Tentler, Aleksey ^a  

^a ROCHESTER INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Attention; Clustering; Habituation; Learning; Motion detection; Spatiotemporal filtering; Video streams

Indexed keywords

HABITUATION; MOTION DETECTION; SPATIOTEMPORAL FILTERING; VIDEO STREAMS;

COMPUTER SCIENCE; COMPUTER VISION; IMAGE PROCESSING; MONITORING; NEURAL NETWORKS; REAL TIME SYSTEMS; VELOCITY;

VIDEO SIGNAL PROCESSING;

EID: 8844253872     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.532741     Document Type: Conference Paper

References (23)

1. Medioni,G., Cohen, I., Brmond, F., Hongeng, S., and Nevatia R. Event Detection and Analysis from Video Streams. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23: 8, 873-889. 2001.
2. Haering, N. C., Qian, R.J., and Sezan, M. I. A Semantic Event Detection Approach and Its Application to Detecting Hunts in Wildlife Video. In IEEE Transactions on Circuits and Systems for Video technology, 10:857-868. 1999
3. Stauffer, C., and Grimson, E. Learning Patterns of Activity Using Real-Time Tracking. In IEEE Transactions on Pattern Analysis and Machine Intelligence. 22(8):747-757. 2000
4. Tender A., Vaingankar V., Gaborski R., and Teredesai A. Event Detection in Video Sequences of Natural Scenes. In IEEE Western New York Image Processing Workshop, Rochester, New York 2003
5. Siddle, D. A. T., Kuiack, M. and Kroese, S. B. The Orienting reflex, (pp. 149-170). In Physiological Correlates of Human Behaviour. Edited by Gale A. and Edwards, J. Academic Press: London. 1983
6. Crook, P. Spotting Novelty: A Neural Network Model for Familiarity Discrimination. 2000
7. Wang D.L. Habituation. Arbib M.A. (ed.), The Handbook of Brain Theory and Neural Networks. 441-444, MIT Press. 1995
8. Marsland, S. Nehmzow, U. and Shapiro, J. A model of habituation applied to mobile robots. In Proceedings of Towards Intelligent Mobile Robots. Bristol, UK. 1999
9. Koch, C., and Ullman S. Shifts in selective visual attention: towards the underlying neural circuitry. Human Neurobiology. 4:219-227. 1985
10. Itti L., and Koch C. Computational modeling of visual attention. Nature Neuroscience Review., 2(3):194-203. 2001
11. Gaborski, R., Vaingankar V.S.; and Canosa, R.L. Goal Directed Visual Search Based on Color Cues: Co-operative Effects of Top-down & Bottom-up Visual Attention. In Proceedings of the Artificial Neural Networks in Engineering, Rolla, Missouri. Vol 13, pp: 613-618, 2003
12. Palmer S., Vision Science: Photons to Phenomenology, MIT press 1999.
13. Young, R. A, Lesperance, R. M., and Meyer, W. W. The Gaussian Derivative model for spatial-temporal vision: I. Cortical Model. Spatial Vision, 14(3,4):261-319. 2001
14. Young R. A. and Lesperance, R. M. A physiological model of motion analysis for machine vision, in Human Vision, Visual Processing and Digital Display, in Proc. SPIE, p 48-123, San Jose, CA. SPIE- The International Society for Optical Engineering. Invited address. 1993
15. Adelson, E.H. and Bergen, J.R. Spatiotemporal energy models for the perception of motion. Journal of Optical Society of America 2:284-321. 1985
16. Petkov N, Westenberg M A. Computer Analysis of Images and Patterns, Lecture Notes in Computer Science, Vol. LNCS 2756, Springer-Verlag Berlin Heidelberg, pp. 762-769, 2003
17. Adelson, E. H., and Bergen, J. R., The extraction of Spatiotemporal energy in human and machine vision, Proceedings of workshop on Motion: Representation and Analysis (pp. 151-155), Charleston, SC. 1986.
18. Markou, M. and Singh, S. Novelty Detection: A Review, Part I: Statistical Approaches, Signal Processing. Forthcoming. 2003
19. Yamanishi, K., and Takeuchi, J. A unifying framework for detecting outliers and change points from non-stationary time series data. In Proc. of the Eighth ACM SIGKDD, ACM Press. 676-681. 2002
20. Ma, J., and Perkins, S. Online Novelty Detection on Temporal Sequences. In Proc. of the Ninth ACM SIGKDD, ACM Press. 613-618. 2003
21. Oh, J; Lee, J. and Kote S. Real Time Video Data Mining for Surveillance Video Streams. In Proceedings of the Seventh Pacific-Asia Conference on Knowledge Discovery and Data Mining, 222-233. Seoul, Korea: Springer-Verlag, 2003
22. Kohonen, T. Self-Organization and Associative Memory. New York: Springer-Verlag. 1988
23. Vaingankar V. S, Chaoji V, Gaborski R S, Teredesai A M. Cognitively Motivated Habituation for Novelty Detection in Video, NIPS Workshop on 'Open Challenges in Cognitive Vision'. Whistler, BC, Canada, December 2003