Automatic indexing and recognition of re-broadcasted video programs through visual and temporal features

In this paper, we describe methods for identification of rebroadcasted video sequences. The methods are applicable to real-time monitoring of video streams, or to searching of large collections. The techniques we present are fast and insensitive to video degradation, making them ideal for re-broadcasted video search. Experiments on large quantities of real-world video data demonstrate that our approach is robust and effective, even for short queries or queries that have been edited or degraded. By using dynamic programming and N-gram matching approaches we identify regions of similarity in video signatures efficiently and accurately in order to identify rebroadcasted videos, even when these regions constitute only a small section of the clip being searched.