Highlight detection in soccer video using web-casting text

Highlight detection is a challenge task in soccer video analysis. Using Web-casting text as external knowledge is proved to be a short cut to achieve both efficiency and effectiveness. Based on the previous framework using Web-casting text, we have improved the processes of video time detection and highlight boundary detection. Our method can detect the transparent time bar and can achieve acceptable precision in highlight boundary detection though the Web text time is not accurate at all. This progress can make the framework more robust in practice.

[1]  Baoxin Li,et al.  Automatic detection of replay segments in broadcast sports programs by detection of logos in scene transitions , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[2]  Wen Gao,et al.  Jersey number detection in sports video for athlete identification , 2005, Visual Communications and Image Processing.

[3]  A. Murat Tekalp,et al.  Generic Event Detection in Sports Video using Cinematic Features , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.

[4]  Lei Wang,et al.  Offense based temporal segmentation for event detection in soccer video , 2004, MIR '04.

[5]  Tat-Seng Chua,et al.  The fusion of audio-visual features and external knowledge for event detection in team sports video , 2004, MIR '04.

[6]  Mohan S. Kankanhalli,et al.  Creating audio keywords for event detection in soccer video , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[7]  Tat-Seng Chua,et al.  Fusion of Multiple Asynchronous Information Sources for Event Detection in Soccer Video , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[8]  Changsheng Xu,et al.  Video Clock Time Reconition Based on Temporal Periodic Pattern Change of the Digit Characters , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[9]  Noboru Babaguchi,et al.  Personalized abstraction of broadcasted American football video by highlight selection , 2004, IEEE Transactions on Multimedia.

[10]  Chng Eng Siong,et al.  Automatic generation of personalized music sports video , 2005, MULTIMEDIA '05.

[11]  Peter J. L. van Beek,et al.  Detection of slow-motion replay segments in sports video for highlights generation , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Shih-Fu Chang,et al.  Structure analysis of soccer video with domain knowledge and hidden Markov models , 2004, Pattern Recognit. Lett..

[13]  Changsheng Xu,et al.  Live sports event detection based on broadcast video and web-casting text , 2006, MM '06.

[14]  Alan Hanjalic,et al.  Generic approach to highlights extraction from a sport video , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[15]  Shih-Fu Chang,et al.  Algorithms and system for segmentation and structure analysis in soccer video , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[16]  Chung-Lin Huang,et al.  Semantic analysis of soccer video using dynamic Bayesian network , 2006, IEEE Transactions on Multimedia.

[17]  A. Murat Tekalp,et al.  Automatic Soccer Video Analysis and Summarization , 2003, IS&T/SPIE Electronic Imaging.

[18]  David S. Doermann,et al.  Identifying sports videos using replay, text, and camera motion features , 1999, Electronic Imaging.