Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Automatic detection of 'Goal' segments in basketball videos
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
A mid-level representation framework for semantic sports video analysis
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Maximum entropy model-based baseball highlight detection and classification
Computer Vision and Image Understanding - Special issue on event detection in video
Replay Detection in Broadcasting Sports Video
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
A unified framework for semantic shot representation of sports video
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Automatic video summarization of sports videos using metadata
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
Automatically selecting shots for action movie trailers
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Fast analysis of scalable video for adaptive browsing interfaces
Computer Vision and Image Understanding
Highlight Ranking for Broadcast Tennis Video Based on Multi-modality Analysis and Relevance Feedback
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Story unit segmentation with friendly acoustic perception
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
Video summarization based on user interaction
Proceddings of the 9th international interactive conference on Interactive television
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Sports video has been extensively studied for its wide viewer-ship and tremendous commercial potentials. Many studies focused on highlight extraction for summarizing a lengthy video. In this paper, we present an advanced highlight analysis system for sports video browsing, in which highlight evaluation and ranking are concerned besides highlight detection. First, we use replay detection to efficiently localize the highlights. Then incorporating with domain-specific knowledge, we adopt several significant cues to evaluate the importance degree of the highlights with support vector regression. Finally, the highlights are ranked with descending sort according to their importance value. The ranking results can provide a hierarchical video browsing and customized content delivery scheme. Initial experimental results on soccer videos show an encouraging performance comparing with human subjective evaluation.