Trajectory based event tactics analysis in broadcast sports video

ABSTRACT

Most of existing approaches on event detection in sports video are general audience oriented. The extracted events are then presented to the audience without further analysis. However, professionals, such as soccer coaches, are more interested in the tactics used in the events. In this paper, we present a novel approach to extract tactic information from the goal event in broadcast soccer video and present the goal event in a tactic mode to the coaches and sports professionals. We first extract goal events with far-view shots based on analysis and alignment of web-casting text and broadcast video. For a detected goal event, we employ a multi-object detection and tracking algorithm to obtain the players and ball trajectories in the shot. Compared with existing work, we proposed an effective tactic representation called aggregate trajectory which is constructed based on multiple trajectories using a novel analysis of temporal-spatial interaction among the players and the ball. The interactive relationship with play region information and hypothesis testing for trajectory temporal-spatial distribution are exploited to analyze the tactic patterns in a hierarchical coarse-to-fine framework. The experimental results on the data of FIFA World Cup 2006 are promising and demonstrate our approach is effective.

REFERENCES

• 1: Chua Hock Chuan, Automatic Parsing of TV Soccer Programs, Proceedings of the International Conference on Multimedia Computing and Systems, p.167, May 15-18, 1995 [doi>10.1109/MMCS.1995.484921]
• 2: A. Ekin, A. M. Tekalp, and R. Mehrotra, "Automatic soccer video analysis and summarization," IEEE Trans. Image Processing, vol. 12, no. 7, pp. 796--807, 2003.
• 3: Lexing Xie , Peng Xu , Shih-Fu Chang , Ajay Divakaran , Huifang Sun, Structure analysis of soccer video with domain knowledge and hidden Markov models, Pattern Recognition Letters, v.25 n.7, p.767-775, May 2004 [doi>10.1016/j.patrec.2004.01.005]
• 4: Yong Rui , Anoop Gupta , Alex Acero, Automatically extracting highlights for TV Baseball programs, Proceedings of the eighth ACM international conference on Multimedia, p.105-115, October 2000, Marina del Rey, California, United States [doi>10.1145/354384.354443]
• 5: Jürgen Assfalg , Marco Bertini , Carlo Colombo , Alberto Del Bimbo , Walter Nunziati, Semantic annotation of soccer videos: automatic highlights identification, Computer Vision and Image Understanding, v.92 n.2-3, p.285-305, November/December 2003 [doi>10.1016/j.cviu.2003.06.004]
• 6: N. Babaguchi, Y. Kawai, T. Ogura, and T. Kitahashi, "Personalized abstraction of broadcasted American football video by highlight selection," IEEE Trans. Multimedia, vol. 6, no. 4, pp. 575--586, 2004.
• 7: Changsheng Xu , Jinjun Wang , Kongwah Wan , Yiqun Li , Lingyu Duan, Live sports event detection based on broadcast video and web-casting text, Proceedings of the 14th annual ACM international conference on Multimedia, October 23-27, 2006, Santa Barbara, CA, USA [doi>10.1145/1180639.1180699]
• 8: Guangyu Zhu , Changsheng Xu , Qingming Huang , Wen Gao , Liyuan Xing, Player action recognition in broadcast tennis video with applications to semantic analysis of sports game, Proceedings of the 14th annual ACM international conference on Multimedia, October 23-27, 2006, Santa Barbara, CA, USA [doi>10.1145/1180639.1180728]
• 9: A. Hanjalic, "Adaptive extraction of highlights from a sport video based on excitement modeling," IEEE Trans. Multimedia, vol. 7, no. 6, pp. 1114--1122, 2005.
• 10: Ling-Yu Duan , Min Xu , Tat-Seng Chua , Qi Tian , Chang-Sheng Xu, A mid-level representation framework for semantic sports video analysis, Proceedings of the eleventh ACM international conference on Multimedia, November 02-08, 2003, Berkeley, CA, USA [doi>10.1145/957013.957020]
• 11: M. Xu, L. Duan, C. Xu, and Q. Tian, "A fusion scheme of visual and auditory modalities for event detection in sports video," in Proc. Int. Conf. Acoustics, Speech, and Signal Processing, vol. 3, 2003, pp. 189--192.
• 12: Pascual J. Figueroa , Neucimar J. Leite , Ricardo M. L. Barros, Tracking soccer players aiming their kinematical motion analysis, Computer Vision and Image Understanding, v.101 n.2, p.122-135, February 2006 [doi>10.1016/j.cviu.2005.07.006]
• 13: G. Sudhir , John C. M. Lee , Anil K. Jain, Automatic Classification of Tennis Video for High-level Content-based Retrieval, Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98), p.81, January 03-03, 1998
• 14: Jenny R. Wang , Nandan Parameswaran, Analyzing Tennis Tactics from Broadcasting Tennis Video Clips, Proceedings of the 11th International Multimedia Modelling Conference, p.102-106, January 12-14, 2005 [doi>10.1109/MMMC.2005.20]
• 15: P. Wang, R. Cai, and S. Q. Yang, "A tennis video indexing approach through pattern discovery in interactive process," in Proc. Pacific-Rim Conf. Multimedia, 2004, pp. 49--56.
• 16: T. Taki, J. Hasegawa, and T. Fukumura, "Development of motion analysis system for quantitative evaluation of teamwork in soccer games," in Proc. Int. Conf. Image Processing, vol. 3, 1996, pp. 815--818.
• 17: Shoji Hirano , Shusaku Tsumoto, Finding interesting pass patterns from soccer game records, Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, p.209-218, September 20-24, 2004, Pisa, Italy
• 18: Chan-Hyun Kang , Jung-Rae Hwang , Ki-Joune Li, Trajectory Analysis for Soccer Players, Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops, p.377-381, December 18-22, 2006 [doi>10.1109/ICDMW.2006.160]
• 19: http://soccernet.espn.go.com
• 20: Yiqun Li , Changsheng Xu , Kong Wah Wan , Xin Yan , Xinguo Yu, Reliable Video Clock Time Recognition, Proceedings of the 18th International Conference on Pattern Recognition, p.128-131, August 20-24, 2006 [doi>10.1109/ICPR.2006.993]
• 21: G. Zhu, C. Xu, Q. Huang, and W. Gao, "Automatic multi-player detection and tracking in broadcast sports video using support vector machine and particle filter," in Proc. Int. Conf. Multimedia & Expo, 2006, pp. 1629--1632.
• 22: D. Liang, Y. Liu, Q. Huang, and W. Gao, "A scheme for ball detection and tracking in broadcast soccer video," in Proc. Pacific-Rim Conf. Multimedia, 2005, pp. 864--875.
• 23: F. Dufaux and J. Konrad, "Efficient, robust, and fast global motion estimation for video coding," IEEE Trans. Image Processing, vol. 9, no. 3, pp. 497--501, 2000.
• 24: Jinjun Wang , Changsheng Xu , Engsiong Chng , Kongwah Wah , Qi Tian, Automatic replay generation for soccer video broadcasting, Proceedings of the 12th annual ACM international conference on Multimedia, October 10-16, 2004, New York, NY, USA [doi>10.1145/1027527.1027535]
• 25: G. A. Korn and T. M. Korn, Math. Handbook for Scientists and Engineers, New York: McGraw-Hill, 1968.
• 26: John P. Chin , Virginia A. Diehl , Kent L. Norman, Development of an instrument measuring user satisfaction of the human-computer interface, Proceedings of the SIGCHI conference on Human factors in computing systems, p.213-218, May 15-19, 1988, Washington, D.C., United States [doi>10.1145/57167.57203]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.8 Scene Analysis
          Subjects: Motion

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.10 Vision and Scene Understanding
            Subjects: Video analysis
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.8 Scene Analysis
          Subjects: Tracking; Object recognition

General Terms:
Algorithms, Experimentation, Measurement, Performance

Keywords:
broadcast video, event detection, object tracking, tactics analysis, trajectory analysis