Changsheng Xu
ABSTRACT
Event detection is essential for sports video summarization, indexing and retrieval and extensive research efforts have been devoted to this area. However, the previous approaches are heavily relying on video content itself and require the whole video content for event detection. Due to the semantic gap between low-level features and high-level events, it is difficult to come up with a generic framework to achieve a high accuracy of event detection. In addition, the dynamic structures from different sports domains further complicate the analysis and impede the implementation of live event detection systems. In this paper, we present a novel approach for event detection from the live sports game using web-casting text and broadcast video. Web-casting text is a text broadcast source for sports game and can be live captured from the web. Incorporating web-casting text into sports video analysis significantly improves the event detection accuracy. Compared with previous approaches, the proposed approach is able to: (1) detect live event only based on the partial content captured from the web and TV; (2) extract detailed event semantics and detect exact event boundary, which are very difficult or impossible to be handled by previous approaches; and (3) create personalized summary related to certain event, player or team according to user's preference. We present the framework of our approach and details of text analysis, video analysis and text/video alignment. We conducted experiments on both live games and recorded games. The results are encouraging and comparable to the manually detected events. We also give scenarios to illustrate how to apply the proposed solution to professional and consumer services.
- Y. Rui, A. Gupta, and A. Acero, "Automatically extracting highlights for TV baseball programs", In Proc. of ACM Multimedia, Los Angeles, CA, pp. 105--115, 2000. Google Scholar
Digital Library
- M. Xu, N.C. Maddage, C. Xu, M.S. Kakanhalli, and Q. Tian, "Creating audio keywords for event detection in soccer video", In Proc. of IEEE International Conference on Multimedia and Expo, Baltimore, USA, Vol.2, pp.281--284, 2003. Google ScholarDigital Library
- Y. Gong, L.T. Sin, C.H. Chuan, H.J. Zhang, and M. Sakauchi, "Automatic parsing of TV soccer programs", In Proc. of International Conference on Multimedia Computing and Systems, pp. 167--174, 1995. Google ScholarDigital Library
- A. Ekin, A. M. Tekalp, and R. Mehrotra, "Automatic soccer video analysis and summarization", IEEE Trans. on Image Processing, vol. 12:7, no. 5, pp. 796--807, 2003. Google ScholarDigital Library
- D. Zhang, and S.F. Chang, "Event detection in baseball video using superimposed caption recognition", In Proc. of ACM Multimedia, pp. 315--318, 2002. Google ScholarDigital Library
- J. Assfalg, M. Bertini, C. Colombo, A. Bimbo, and W. Nunziati, "Semantic annotation of soccer videos: automatic highlights identification," Computer Vision and Image Understanding (CVIU), Vol. 92, pp. 285--305, November 2003. Google ScholarDigital Library
- R. Radhakrishan, Z. Xiong, A. Divakaran, Y. Ishikawa, "Generation of sports highlights using a combination of supervised & unsupervised learning in audio domain", In Proc. of International Conference on Pacific Rim Conference on Multimedia, Vol. 2, pp. 935--939, December 2003.Google ScholarCross Ref
- K. Wan, and C. Xu, "Robust soccer highlight generation with a novel dominant-speech feature extractor", In Proc. of IEEE International Conference on Multimedia and Expo, Taipei, Taiwan, pp.591--594, 27-30 Jun. 2004.Google Scholar
- 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. of IEEE International Conference on Acoustics, Speech, & Signal Processing, Hong Kong, China, Vol.3, pp.189--192, 2003.Google Scholar
- K. Wan, C. Xu, "Efficient multimodal features for automatic soccer highlight generation", In Proc. of International Conference on Pattern Recognition, Cambridge, UK, Vol.3, pp.973--976, 23-26 Aug. 2004. Google ScholarDigital Library
- M. Xu, L. Duan, C. Xu, M.S. Kankanhalli, and Q. Tian, "Event detection in basketball video using multi-modalities", In Proc. of IEEE Pacific Rim Conference on Multimedia, Singapore, Vol.3, pp.1526--1530, 15-18 Dec, 2003.Google Scholar
- M. Han, W. Hua, W. Xu, and Y. Gong, "An integrated baseball digest system using maximum entropy method", In Proc. of ACM Multimedia, pp.347--350, 2002. Google ScholarDigital Library
- S. Nepal, U. Srinivasan, and G. Reynolds, "Automatic detection of goal segments in basketball videos, In Proc. of ACM Multimedia, Ottawa, Canada, pp. 261--269, 2001. Google ScholarDigital Library
- J. Wang, C. Xu, E.S. Chng,, K. Wan, and Q. Tian, "Automatic generation of personalized music sports video", In Proc. of ACM International Conference on Multimedia, Singapore, pp.735--744, 6-11 Nov. 2005. Google ScholarDigital Library
- N. Nitta and N. Babaguchi, "Automatic story segmentation of closed-caption text for semantic content analysis of broadcasted sports video," In Proc. of 8th International Workshop on Multimedia Information Systems '02, pp. 110--116, 2002.Google Scholar
- N. Babaguchi, Y. Kawai, and T. Kitahashi, "Event based indexing of broadcasted sports video by intermodal collaboration," IEEE Trans. on Multimedia, Vol. 4, pp. 68--75, March 2002. Google ScholarDigital Library
- N. Nitta, N. Babaguchi, and T. Kitahashi, "Generating semantic descriptions of broadcasted sports video based on structure of sports game," Multimedia Tools and Applications, Vol. 25, pp. 59--83, January 2005. Google ScholarDigital Library
- H. Xu and T. Chua, "The fusion of audio-visual features and external knowledge for event detection in team sports video," In Proc. of Workshop on Multimedia Information Retrieval (MIR'04), Oct 2004. Google ScholarDigital Library
- H. Xu and T. Chua, "Fusion of multiple asynchronous information sources for event detection in soccer video", In Proc. of IEEE ICME'05, Amsterdam, Netherlands, pp.1242--1245, 2005. Google ScholarDigital Library
- http://news.bbc.co.uk/sport2/hi/football/teams/Google Scholar
- http://sports.espn.go.com/Google Scholar
- M. Bertini, R. Cucchiara, A. D. Bimbo, and A. Prati, "Object andevent detection for semantic annotation and transcoding," in Proc.IEEE Int. Conf. Multimedia and Expo, Baltimore, MD, Jul. 2003, pp.421--424. Google ScholarDigital Library
- R. Leonardi and P. Migliorati, "Semantic indexing of multimedia documents," IEEE Multimedia, Vol. 9, pp. 44-51, Apr.-June 2002. Google ScholarDigital Library
- http://soccernet.espn.go.com/Google Scholar
- Y. Tan and et al, "Rapid estimation of camera motion from compressed video with application to video annotation," IEEE Trans. on Circuits and Systems for Video Technology, vol. 10- 1, pp. 133--146, 2000. Google ScholarDigital Library
- Y. Li, C. Xu, K. Wan, X. Yan, and X. Yu, Reliable video clock time recognition, In Proc. of Intl. Conf. Pattern Recognition, Hong Kong, 20--24, Aug. 2006. Google ScholarDigital Library
Index Terms
- Live sports event detection based on broadcast video and web-casting text
Recommendations
Trajectory based event tactics analysis in broadcast sports video
MM '07: Proceedings of the 15th ACM international conference on MultimediaMost 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 ...
Using Webcast Text for Semantic Event Detection in Broadcast Sports Video
Sports video semantic event detection is essential for sports video summarization and retrieval. Extensive research efforts have been devoted to this area in recent years. However, the existing sports video event detection approaches heavily rely on ...
A generic framework for event detection in various video domains
MM '10: Proceedings of the 18th ACM international conference on MultimediaEvent detection is essential for the extensively studied video analysis and understanding area. Although various approaches have been proposed for event detection, there is a lack of a generic event detection framework that can be applied to various ...
Comments