Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
Detection of slow-motion replay segments in sports video for highlights generation
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Efficient MPEG compressed video analysis using macroblock typeinformation
IEEE Transactions on Multimedia
Manipulation and compositing of MC-DCT compressed video
IEEE Journal on Selected Areas in Communications
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
A novel video key-frame-extraction algorithm based on perceived motion energy model
IEEE Transactions on Circuits and Systems for Video Technology
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Efficient data mining for digital video has become increasingly important in recent years. In this paper, we present a new scheme for automatic detection of slow-motion replays in sports video. Several slow-motion features and some newly discovered characteristics of slow-motion segments are exploited to aid the detection. The first step of our method is based on the macroblock motion vector information, while the second step makes use of frame-to-frame difference under an MC-DCT structure to verify the output of the first step. The last step is applied to refine the segment boundaries. Unlike previous approaches, our method has great improvement in both speed and accuracy and a balance between efficiency and simplicity.