Feature statistical retrieval applied to content-based copy identification

In many image or video retrieval systems, the search of similar objects in the database includes a spatial access method to a multidimensional feature space. This step is generally considered as a problem independent of the features and the similarity type. The well known multidimensional nearest neighbor search was also widely studied by the database community as a generic method. In this paper, we propose a novel strategy dedicated to pseudo-invariant features retrieval and more specifically applied to content-based copy identification. The range of a query is computed during the search according to deviation statistics between original and observed features. Furthermore, this approximate search range is directly mapped onto a Hilbert space-filling curve allowing an efficient access to the database. Experimental results give excellent response times for very large databases both on synthetic and real data. This work is used in a TV monitoring system including more than 13000 hours o...

• Type: Conference
• Year: 2004
• Where: ICIP
• Authors: Alexis Joly, Carl Frélicot, Olivier Buisson
• Keywords: Approximate Search Range, Hilbert Space-filling Curve, ICIP 2004, Image Processing, Multidimensional Feature Space, Multidimensional Nearest Neighbor, Spatial Access Method