Automatic partitioning of full-motion video
Multimedia Systems
A new feature weighted fuzzy clustering algorithm
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
A shot boundary detection method for news video based on rough sets and fuzzy clustering
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Performance characterization of video-shot-change detection methods
IEEE Transactions on Circuits and Systems for Video Technology
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Shot boundary detection as the crucial step attracts much more research interests in recent years. To partition news video into shots, many metrics were constructed to measure the similarity among video frames based on all the available video features. However, too many features will reduce the efficiency of the shot boundary detection. Therefore, it is necessary to perform feature reduction before shot boundary detection. For this purpose, the classification method based on clustering algorithm of Variable Precision Rough-Fuzzy Sets and Variable Precision Rough Sets for feature reduction and feature weighting is proposed. According to the particularity of news scenes, shot transition can be divided into three types: cut transition, gradual transition and no transition. The efficiency of the proposed method is extensively tested on UCI data sets and more than 3 h of news programs and 96.2% recall with 96.3% precision have been achieved.