Copy Detection of Immersed Content in Video Databases

Content-Based Copy Detection techniques aim at the identification of modified copies of an original clip in a given database or on the Internet. Usually, a digital fingerprint is computed from the media itself by extracting some features which are later used for the copy detection task. In this paper we propose a system for Video Copy Detection which makes use of several low-level features. In particular we investigate the problem of the detection of copies immersed in dummy multimedia contents. By analyzing the temporal evolution of the selected features, the proposed method detects the relevant part of the query useful for the detection of the original content the query has been extracted from. Experiments conducted on the data set provided by MPEG indicate that a combined use of different features can be useful for isolating immersed copies. Moreover we can see that the various features act differently with respect to the type of modification the video query suffered.