Similarity search of videos based on mixture distributions

摘要

A similarity search method is presented for videos based on their segmentation by clustering. Videos are partitioned into shots by clustering of the set of frames based on color histograms. The performance of this segmentation is improved by addition of temporal information to color data. Videos are represented by mixture distributions and the distance between videos is evaluated by the works needed for transforming one distribution to another one. This distance is used for similarity search of videos. It is also shown for this similarity search that its performance is raised by incorporating temporal information. Finally a filtering method based on an inequality for the distance is devised for speeding up the similarity search.