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Pattern Analysis and Applications

Erschienen in:

01.12.2004 | Theoretical Advances

A framework of joint object tracking and event detection

verfasst von: Ruoyu Roy Wang, Thomas Huang

Erschienen in: Pattern Analysis and Applications | Ausgabe 4/2004

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Abstract

This paper describes a probabilistic framework for simultaneously performing object tracking and event detection in monocular videos. Mathematically, we cast the problem of jointly tracking and detecting semantic events as a principled model-based search problem in a multi-dimensional state space, where the tracking trajectory and event type are discovered via maximum a posteriori (MAP) optimization. The benefit of this approach comes from its combined utilization of particle probabilistic representation, multiple hypothesis retention, efficient particle propagation, and temporal optimization. We present qualitative and quantitative results from realistic video sequences to demonstrate the effectiveness of this approach.

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Naphades MR, Wang RR, Huang TS (2001) Audio-visual query and retrieval: a system that uses dynamic programming and relevance feedback. J Electron Imaging 10:861–870CrossRef

Viterbi AJ (1967) Error bounds for convolutional codes and an asymptotically optimal decoding algorithm. IEEE Trans Inform Theory IT-13:260–269CrossRef

Forney G (1973) The Viterbi algorithm. Proc IEEE 61:268–278

Wolf JK, Viterbi A, Dixon G (1989) Finding the best set of k paths through a trellis with application to multitarget tracking. IEEE Trans Aero Electron Sys 25:287–295CrossRef

Isard M, Blake A (1996) Visual tracking by stochastic propagation of conditional density. In: Proceedings of the 4th European conference on computer vision (Eccv’96), Cambridge, UK, April 1996, pp 343–356

Li B, Chellappa R (2000) Simultaneous tracking and verification via sequential posterior estimation. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2000), Hilton Head Island, South Carolina, June 2000

Doucet A, Godsill S, Andrieu C (2000) On sequential Monte Carlo sampling methods for Bayesian filtering. Stat Comput 10:197–208CrossRef

Godsill S, Doucet A, West M (2001) Maximum a posteriori sequence estimation using Monte Carlo particle filters. Ann Inst Stat Math 52(1):82–96MathSciNet

Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J Roy Stat Soc B 39:1–38

10.

Cham T-J, Rehg JM (1999) A multiple hypothesis approach to figure tracking. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’99), Fort Collins, Colorado, June 1999, pp 239–244

11.

Morris DD, Rehg J (1998) Singularity analysis for articulated object tracking. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’98), Santa Barbara, California, June 1998, pp 289–296

12.

Birchfield S (1998) Elliptical head tracking using intensity gradients and color histograms. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’98), Santa Barbara, California, June 1998, pp 232–237

13.

Comaniciu D, Ramesh V, Meer P (2000) Real-time tracking of nonrigid objects using mean shift. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2000), Hilton Head Island, South Carolina, June 2000, vol 2, pp 142–149

14.

McKenna S, Raja Y, Gong S (1998) Object tracking using adaptive colour mixture models. In: Proceedings of the Asian conference on computer vision (ACCV’98), Hong Kong, China, January 1998

15.

Hager G, Belhumeur P (1996) Real-time tracking of image regions with changes in geometry and illumination. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’96), San Francisco, California, June 1996, pp 88–93

16.

Gavrila DM (2000) Pedestrian detection from a moving vehicle. In: Proceedings of the 6th IEEE European conference on computer vision (Eccv 2000), Dublin, Ireland, June/July 2000

17.

Ju SX, Black MJ, Yacoob Y (1996) Cardboard people: a parameterized model of articulated motion. In: Proceedings of the 2nd international conference on automatic face and gesture recognition (FG’96), Killington, Vermont, October 1996, pp 38–44

18.

Wren C, Azarbayejani A, Darrell T, Pentland A (1997) Pfinder: realtime tracking of the human body. IEEE Trans Pattern Recogn Mach Intell 19(7):780–785CrossRef

19.

Blake A, Isard M (1998) Active contours. Springer, Berlin Heidelberg New York

20.

Toyama K, Blake A (2001) Probabilistic tracking in a metric space. In: Proceedings of the 8th IEEE international conference on computer vision (ICCV 2001), Vancouver, Canada, July 2001, vol 2, pp 50–57

21.

Bobick A, Davis J (2001) The recognition of human movement using temporal templates. IEEE Trans Pattern Recogn Mach Intell 23(3):257–267CrossRef

22.

Polana R, Nelson R (1997) Detection and recognition of periodic, nonrigid motion. Int J Comput Vis 23(3):261–282CrossRef

23.

Chomat O, Crowley JL (1999) Probabilistic recognition of activity using local appearance. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’99), Fort Collins, Colorado, June 1999, vol 2, pp 104–109

24.

Niyogi SA, Adelson EH (1994) Analyzing and recognizing walking figures in XYT. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’94), Seattle, Washington, June 1994, pp 469–474

25.

Gavrila D, Davis L (1996) 3D model-based tracking of humans in action: a multi-view approach. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’96), San Francisco, California, June 1996, pp 73–80

26.

Clarkson B, Pentland A (2000) Framing through peripheral perception. In: Proceedings of the IEEE international conference on image processing (ICIP 2000), Vancouver, Canada, September 2000, vol 3, pp 38–41

27.

Bregler C (1997) Learning and recognizing human dynamics in video sequences. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR’97), San Juan, Puerto Rico, June 1997, pp 568–574

28.

Zelnik-Manor L, Irani M (2001) Event-based analysis of video. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2001), Kauai, Hawaii, December 2001, vol 2, pp 123–130

29.

Medioni G, Cohen I, Bremond F, Hongeng S, Nevatia R (2001) Event detection and analysis from video streams. IEEE Trans Pattern Recogn Mach Intell 23(8):873–889CrossRef

30.

Isard M, Blake A (1998) CONDENSATION—conditional density propagation for visual tracking. Int J Comput Vis 29(1):5–28CrossRef

31.

Bar-Shalom Y, Fortmann TE (1988) Tracking and data association. Academic Press, San Diego, California

32.

Arulampalam MS, Maskell S, Gordon N, Clapp T (2002) A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans Signal Process 50(2):174–188CrossRef

33.

Rabiner LR, Juang BH (1993) Fundamentals of speech recognition. Prentice Hall, Englewood Cliffs, New Jersey

34.

Jesorsky O, Kirchberg K, Frischholz R (2001) Robust face detection using the Hausdorff distance. In: Proceedings of the 3rd international conference on audio- and video-based biometric person authentication (AVBPA 2001), Halmstad. Sweden, June 2001, pp 90–95

35.

Johnson SC (1967) Hierarchical clustering schemes. Psychometrika 2:241–254MATH

36.

D’andrade R (1978) U-statistic hierarchical clustering. Psychometrika 4:58–67

Titel: A framework of joint object tracking and event detection
verfasst von: Ruoyu Roy Wang
Thomas Huang
Publikationsdatum: 01.12.2004
Verlag: Springer-Verlag
Erschienen in: Pattern Analysis and Applications / Ausgabe 4/2004
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-004-0231-4

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