Scalable mining of large video databases using copy detection

Sébastien Poullot, Michel Crucianu, Olivier Buisson
2008 Proceeding of the 16th ACM international conference on Multimedia - MM '08  
Mining the video content itself can bring to light important information regarding the internal structure of large video databases, compensating for a lasting absence of extensive and reliable annotations. Many valuable links between video segments can be identified by content-based copy detection methods, where "copies" are transformed versions of original video sequences. To make this approach viable for large video databases, we put forward a new mining method relying on the definition of a
more » ... ompact keyframe-level descriptor and of a specific index structure. The performance obtained in detecting links between video segments is evaluated with the help of a ground truth and several illustrations are given. The scalability of the approach is then demonstrated for databases of up to 10,000 hours of video.
doi:10.1145/1459359.1459368 dblp:conf/mm/PoullotCB08 fatcat:zbxi35bzibegdbe2wfitufaccu