Abstract
In this paper, we present a real-time sports analysis system, which not only recognizes the semantic events, but also concludes the behavior, like player’s tactics. To this end, we propose an advanced multiple-player tracking algorithm, which addresses two improvements on practical problems: (1) updating of the player template so that it remains a good model over time, and (2) adaptive scaling of the template size depending on the player motion. In this algorithm, we obtain the initial locations of players in the first frame. The tracking is performed by considering both the kinematic constraints of the player and the color distribution of appearance, thereby achieving promising results. We demonstrate the performance of the proposed system by evaluating it for double tennis matches where the player count and the resulting occlusions are challenging.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Needham, C., Boyle, R.: Tracking multiple sports players through occlusion, congestion and scale. In: Proc. 12th British Machine Vision Conference (BMVA) 2001, vol. 1, pp. 93–102 (2001)
Pan, H., Beek, P., Sezan, M.: Detection of slow-motion replay segments in sports video for highlights generation. In: Proc. ICASSP 2001, Salt Lake City, UT (May 2001)
Gong, Y., Sin, L., Chuan, C., Zhang, H.: Automatic parsing of soccer programs. In: Proc. IEEE Int. Conf. Mult. Comput. Syst., pp. 167–174 (1995)
Sudhir, G., Lee, C., Jain, K.: Automatic classification of tennis video for high-level content-based retrieval. In: Proc. IEEE international workshop on content based access of image and video databases, pp. 81–90 (1998)
Kijak, E., Oisel, L., Gros, P.: Temporal structure analysis of broadcast tennis video using hidden Markov models. In: Proc. SPIE Storage and Retrieval for Media Databases 2003, pp. 289–299 (January 2003)
Kang, J., Cohen, I., Medioni, G.: Soccer player tracking across uncalibrated camera streams. In: Proc. IEEE Int. Worksh. Visual surveillance and perform. eval. of tracking and surveillance (October 2003)
Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based object tracking. IEEE Trans. Pattern Analysis Machine Intell. 25(5), 564–575 (2003)
Matthews, I., Ishikawa, T., Baker, S.: The template update problem. IEEE Trans. Pattern Analysis Machine Intell. 26(6), 810–815 (2004)
Han, J., Farin, D., de With, P.H.N.: Multi-level analysis of sports video sequences. In: Proc. SPIE Multimedia content analysis management and retrieval, San Jose (CA), vol. 6073, No. 607303, pp. 1–12 (January 2006)
Farin, D., Han, J., de With, P.H.N.: Fast camera-calibration for the analysis of sports sequences. In: Proc. IEEE Int. conf. Mult. Expo (ICME 2005), Amsterdam, pp. 482–485 (July 2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Han, J., de With, P.H.N. (2006). Content-Based Model Template Adaptation and Real-Time System for Behavior Interpretation in Sports Video. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_43
Download citation
DOI: https://doi.org/10.1007/11864349_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44630-9
Online ISBN: 978-3-540-44632-3
eBook Packages: Computer ScienceComputer Science (R0)