Unsupervised event discrimination based on nonlinear temporal modeling of activity content

Pattern Analysis and Applications

Volumn 7, Issue 4, 2005, Pages 402-410

  Bruno, Eric ^a   Moenne Loccoz, Nicolas ^a   Marchand Maillet, Stéphane ^a  

^a UNIVERSITY OF GENEVA   (Switzerland)

Author keywords

Activity recognition; Motion estimation; SVM learning; Video analysis; Video similarity measure

Indexed keywords

EID: 23944499865     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10044-005-0242-9     Document Type: Article

References (26)

1. Black MJ, Jepson AD (1998) A probabilistic framework for matching temporal trajectories: Condensation-based recognition of gestures and expressions. In: Burkhardt H, Neumann B (eds) European conference on computer vision, ECCV-98, vol 1406 of LNCS-series, Springer, Freiburg, pp 909-924
2. Bruno E, Pellerin D (2001) Global motion model based on B-spline wavelets: Application to motion estimation and video indexing. In: Proceedings of the 2nd international symposium on image and signal processing and analysis, ISPA'01, June 2001
3. Bruno E, Pellerin D (2002) Video structuring, indexing and retrieval based on global motion wavelet coefficients. In: Proceedings of international conference of pattern recognition (ICPR), Quebec City, August 2002
4. Chang SF, Chen W, Meng HJ, Sundaram H, Zhong D (1998) A fully automated content-based video search engine supporting spatio-temporal queries. IEEE Trans Circuits Syst Video Technol 8(5):602-615
5. Chomat O, Crowley J (1999) Probabilistic recognition of activity using local appearance. In: Proceedings of IEEE conference on computer vision and pattern recognition, CVPR'99, June 1999, pp 104-109
6. Duric Z, Rivlin E, Rosenfeld A (2000) Qualitative description of camera motion from histograms of normal flow. In: ICPR00, vol 111
7. Fablet R, Bouthemy P, Perez P (2002) Non parametric motion characterization using temporal gibbs models for content-based video indexing and retrieval. IEEE Trans Image Process 11(4):393-407
8. Gardenfors P (1996) Conceptual spaces as a basis for cognitive semantics. In: Clark A et al (eds) Philosophy and cognitive science. Kluwer, Dordrecht
9. Hampapur A, Gupta A, Horowitz B, Shu C, Fuller C, Bach J, Gorkani M, Jain R (1997) Virage video engine. In: Proceedings of SPIE conference on storage and retrieval for image and video databases, vol 3022, San-Jose, pp 188-197, February 1997
10. Horn BKP, Schunk BG (1981) Determining optical flow. Artif Intell 17:185-204
11. Jain AK, Vailaya A, Wei X (1999) Query by video clip. Multimedia Syst 7(5):369-384
12. Janvier B, Bruno E, Marchand-Maillet S, Pun T (2003) Information-theoretic framework for the joint temporal partioning and representation of video data. In: Proceedings of the European conference on content-based multimedia indexing, CBMI'03, September 2003
13. Moënne-Loccoz N, Janvier B, Marchand-Maillet S, Bruno E (2004) Managing video collections at large. In: Proceedings of the 1st workshop on computer vision meets databases CVDB'04, Paris, France, 2004
14. Mukherjee S, Osuna E, Girosi F (1997) Nonlinear prediction of chaotic time series using support vector machines. In: Proceeding of IEEE neural networks for signal processing, NNSP'97, September 1997, pp 24-26
15. Odobez J-M, Bouthemy P (1995) Robust multiresolution estimation of parametric motion models. J Visual Commun Image Represent 6(4):348-365
16. Roach M, Mason J, Xu L-Q, Stentiford FWM (2002) Recent trends in video analysis: A taxonomy of video classification problems. In: Proceedings of the 6th IASTED international conference on internet and multimedia systems and applications, August 2002
17. Rui Y, Anandan P (2000) Segmenting visual actions based on spatio-temporal motion patterns. In: Proceedings of IEEE conference on computer vision and pattern recognition, CVPR'00, vol 1, Hilton Head, SC, pp 111-118, June 2000
18. Smola A, Scholkopf B (1998) A tutorial on support vector regression. Neurocolt2 technical report nc2-tr-1998-030
19. Srinivasan S, Ponceleon D, Amir A, Petkovic D (1999) What is in that video anyway? In search of better browsing. In: Proceedings of IEEE international conference on multimedia computing and systems, Florence, Italy, June 1999, pp 388-392
20. Taskiran C, Chen J-Y, Albiol A, Torres L, Bouman CA, Delp EJ (2004) Vibe: A compressed video database structured for active browsing and search. IEEE Trans Multimedia 1(6):103-118
21. Vapnik V (1995) The nature of statistical learning theory. Springer, Berlin heidelberg New York
22. Vasconcelos N, Lippman A (1997) Spatiotemporal motion model for video summarization. In: Proceedings of IEEE conference on computer vision and pattern recognition, CVPR'97, Santa Barbara
23. Vinod VV (1998) Activity based video shot retrieval and ranking. In: ICPR 98, pp 682-684
24. Wu YT, Kanade T, Li CC, Cohn J (2000) Image registration using wavelet-based motion model. Int J Comput Vis 38(2):129-152
25. Yacoob Y, Black MJ (1999) Parameterized modeling and recognition of activities. Comput Vis Image Understand 2(73):232-247
26. Zelni-Manor L, Irani M (2001) Event-based analysis of video. In: Proceedings of IEEE conference on computer vision and pattern recognition, CVPR'01, vol 2, Kauai Mariott, Hawai, December 2001, pp 123-130