Cognitively motivated novelty detection in video data streams

Multimedia Data Mining and Knowledge Discovery

Volumn , Issue , 2007, Pages 209-233

  Kang, James M ^a   Ahmad, Muhammad Aurangzeb ^b   Teredesai, Ankur ^b   Gaborski, Roger ^b  

^a University of Minnesota   (United States)

^b ROCHESTER INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84861620807     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-84628-799-2_11     Document Type: Chapter

References (33)

1. Applied Science Laboratories [homepage on the Internet] Available from: http://www.a-s-l.com
2. Burl MC. Mining patterns of activity from video data. SIAM Int. Conf. on Data Mining, April 2004.
3. Cooper M, Foote J, Girgensohn A, Wilcox L. Temporal event clustering for digital photo collections. In: Proceedings of the 11th ACM International Conference on Multimedia, Berkeley, CA, 2003, pp. 364-373.
4. Crook P, Marsland S, Hayes G, Nehmzow U. A tale of two filters-On-line Novelty Detection. In: Proceedings of International Conference on Robotics and Automations (ICRA'02), Washington, DC, 2002:3894-3900.
5. Detyniecki M. Discovering indexing rules for video-news. In: Proceedings of the European SymposiumonIntelligentTechnologies, Hybrid Systems and their implementationon Smart Adaptive Systems-EUNITE'2002, Algarve, Portugal, September, 2002:44-6.
6. Diehl CP, Hampshire JP II. Real-time object classification and novelty detection for collaborative video surveillance. In: Proceedings of the 2002 International Joint Conference on Neural Networks, 3:2620-2625.
7. Furht B, Saksobhavivat P. A fast content-based video and image retrieval technique over communicationchannels. In: Proc. of SPIE Symposium on Multimedia Storage and Archiving Systems, Boston, MA, November 1998.
8. Gaborski R, Vaingankar V, Chaoji V, Teredesai A, Tentler T. VENUS: A system for novelty detection in video streams with learning. In: Proceedings of the 17th International FLAIRS Conference, South Beach, FL, 2004.
9. Journal of Net Centric Warfare [homepage on the Internet] Navy SEALs Using New Video Storage and Editing Laptop [cited 2005 February 14] Available from http://www.isrjournal.com/story.php?F=658407
10. Hayashi A, Nakashima R, Kanbara T, Suematsu N. Multi-object motion pattern classification for visual surveillance and sports video retrieval. In: Proceedings of the 15th International Conference on Vision Interface, Calgary, Canada, 2002.
11. Haering NC, Qian RJ, Sezan MI. ASemantic Event Detection Approachand Its Application to Detecting Hunts in Wildlife Video. IEEE Transactions on Circuits and Systems for Video Technology, 1999;10:857-868.
12. Keim D, Sips M, Ankerst M. Visual data mining. In: Visualization Handbook, Eds. Johnson C. R., Hansen C. D., Academic Press, 2004.
13. Itti L, Koch C. Computational modeling of visual attention. Nature Neuroscience Review; 2001;2(3):194-203.
14. Kohonen T. Self-Organization and Associative Memory. New York: Springer-Verlag; 1988.
15. VirtualDub [homepage on the Internet]. Lee A. Available from: http://www.virtualdub.org
16. Lin J, Keogh E, Truppel W. Clustering of streaming time series is meaningless. In: Proceedings of the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 2003;56-65.
17. TechTrax [homepage on the Internet]. Holographic Video Storage. TechTrax; c2002-2005 [cited 2005 Dec. 9] Available from: http://pubs.logicalexpressions. com/Pub0009/LPMArticle.asp?ID=118
18. Marsland S, Nehmzow U, Shapiro J. Detecting novel features of an environment using habituation. In: Proceedings of Simulation of Adaptive Behavior, MIT Press 2000;189-198.
19. Medioni G, Cohen I, Brmond F, Hongeng S, Nevatia R. Event detection and analysis from video streams. IEEE Transactions on Pattern Analysis and Machine Intelligence 2001;23(8):873-889.
20. Mukherjea S, Hirata K, Hara Y. 2000. Using clustering and visualization for refining the results of a WWW image search engine. In: Proceedings of the CIKM 1998 Workshop on New Paradigms in Information Visualization and Manipulation (NPIV 1998), Nov. 3-7, 1998 ACM. 1998;29-35.
21. Nairac A, Corbett-Clark T, Ripley R, Townsend N, Tarassenko L. Choosing an appropriate model for novelty detection. In: Proceedings of the 5th IEEE International Conference on Artificial Neural Networks, Cambridge, 1997;227-232.
22. Qiu G, Ye L, Feng X. Fast image indexing and visual guided browsing. In: Third International Workshop on Content-Based Multimedia Indexing, Sep. 22-24, 2003 IRISA, Rennes, France.
23. S. Singh, M. Markou. An approach to novelty detection applied to the classification of image regions. IEEE Trans. Knowledge Data Eng. 16(4); Apr, 2004;396-407.
24. Streamload [homepage on the Internet]. Available from: http://www.streamload.com
25. Stauffer C, Grimson E. Learning Patterns of Activity Using Real-Time Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2000;22(8):747-757.
26. Sun X, Manjunath BS, Divakaran A. Representation of motion activity in hierarchical levels for video indexing and filtering. In: Proceedings of IEEE International Conference on Image Processing (ICIP), Rochester, NY, Sep. 2002:149-152.
27. Tarassenko L. Novelty detection for the identification of masses in mammograms. In: Proceedings of the 4th IEE International Conference on Artificial Neural Networks, Cambridge, UK, 1995, 4:442-447.
28. Tentler A, Vaingankar V, Gaborski R, Teredesai A. Event Detection in Video Sequences of Natural Scenes. In: Western New York Image Processing Workshop, Rochester, New York, 2003.
29. Tobii Technology. [homepage on the Internet]. Available from: http://www.tobii.se.
30. Uchihashi S, Foote J, Girgensohn A, Boreczky J. 1999. Video Manga: Generating Semantically Meaningful Video Summaries. In: Proceedings ACM Multimedia, (Orlando, FL) ACM Press, October 30, 1999;383-392.
31. Young RA, Lesperance RM, Meyer WW, The Gaussian Derivative model for spatialtemporal vision: I. Cortical Model. Spatial Vision, 2001;14(3, 4);261-319.
32. Zhu X, Fan J, Elmagarmid AK, Wu X. Hierarchical video content description and summarization using unified semantic and visual similarity. Multimedia Syst. 2003;9(1):31-53.
33. Zhu L, Rao A, Zhang A. Advanced feature extraction for Keyblock-based image retrieval. In: Proceedings of the 2000 ACM Workshops on Multimedia, Los Angeles, CA, 2000, pp. 179-183.