Abstract
Pattern recognition and object tracking play very important roles in various applications, such as motion capture, object detection/recognition, video surveillance, and human computer interface. One very useful method that is rarely mentioned in literature is performing recognition from the motion cue. In many situations, the motion of an object is very representative and informative; therefore, it is possible to identify the object and its behavior from its motion. In this paper, we propose an original method to both identify and track an object in dynamic scenes. The method works on the situations with occlusions, appearance changes and global camera motions. It does not require prior segmentation or initialization. We test this method on a video database containing 18 World Cup soccer videos recorded from TV to detect and track the soccer ball. The results are satisfying. The results are also integrated into a video indexing system and the improvement on video retrieval is described.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berger, A.L., Della Pietra, S.A., Della Pietra, V.J.: A maximum entropy approach to natural language processing. Computational Linguistics 22 (1996)
Dean, G.C.: An introduction to Kalman filters measurement and control, vol. 19, pp. 69–73
Forsyth, D.A., Ponce, J.: Computer Vision: A Modern Approach (2002)
Gong, Y., Sin, L.T., Chuan, C.H., Sakauchi, M.: Automatic parsing of TV soccer programs. In: IEEE International Conference on Multimedia Computing and Systems, pp. 167–174 (1995)
Hua, W., Han, M., Gong, Y.: Baseball Scene classification using multimedia features. In: Proc. IEEE Int’l Conf. on Multimedia and Expo (2002)
Isard, M., Blake, A.: CONDENSATION – conditional density propagation for visual tracking. Int. J. Computer Vision 29(1), 5–28
Jaimes, A., Chang, S.F.: Automatic selection of visual features and classifiers. In: SPIE Conference on Storage and Retrieval for Media Databases (2000)
Ngo, C.H., Pong, T.C., Zhang, H.J.: On clustering and retrieval of video shots. ACM Press, New York (2001)
Peleg, S., Herman, J.: Panoramic mosaics by manifold projection. In: Computer Vision and Pattern Recognition (CVPR), pp. 338–343 (1997)
Pingali, G., Opalach, A., Jean, Y.: Ball tracking and virtual replays for innovative tennis broadcasts. In: Proceedings of the International Conference on Pattern Recognition
Retz-Schmidt, G.: A replai of soccer: Recognizing intentions in the domain of soccer games. In: Proc. European Conference on Artificial Intelligence, pp. 455–457
Shi, J., Malik, J.: Motion Segmentation and Tracking Using Normalized Cuts. In: International Conference on Computer Vision, ICCV (1998)
Tovinkere, V., Qian, R.J.: Detecting semantic events in soccer games: Towards a complete solution. In: IEEE International Conference on Multimedia and Expo (2001)
Utsumi, O., Miura, K., Ide, I., Sakai, S., Tanaka, H.: An object detection method for describing soccer games from video. In: Proc. IEEE ICME 2002 (2002)
Wu, Y., Huang, T.S.: A Co-inference approach to robust visual tracking. In: Proc. IEEE Int’l Conf. on Computer Vision, Vancouver, Canada, vol. II, pp. 26–33
Xu, P., Xie, L., Chang, S.-F., Divakaran, A., Vetro, A., Sun, H.: Algorithms and systems for segmentation and structure analysis in soccer video. In: ICME 2001 (2001)
Yow, D., Yeo, B.-L., Yeung, M., Liu, B.: Analysis and presentation of soccer highlights from digital video. In: Proc. Asian Conference on Computer Vision
Zhong, D., Chang, S.F.: Structure analysis of sports video using domain models. In: IEEE Conference on Multimedia and Expo, pp. 920–923 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, T., Han, M., Hua, W., Gong, Y., Huang, T.S. (2003). A New Tracking Technique: Object Tracking and Identification from Motion. In: Petkov, N., Westenberg, M.A. (eds) Computer Analysis of Images and Patterns. CAIP 2003. Lecture Notes in Computer Science, vol 2756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45179-2_20
Download citation
DOI: https://doi.org/10.1007/978-3-540-45179-2_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40730-0
Online ISBN: 978-3-540-45179-2
eBook Packages: Springer Book Archive