Statistical similarity search applied to content-based video copy detection

—Content-based copy detection (CBCD) is one of the emerging multimedia applications for which there is a need of a concerted effort from the database community and the computer vision community. Recent methods based on interest points and local fingerprints have been proposed to perform robust CBCD of images and video. They include two steps: the search of similar fingerprints in the database and a voting strategy that merges all the local results in order to perform a global decision. In most image or video retrieval systems, the search of similar features in the database is performed by a geometrical query in a multidimensional index structure. Recently, the paradigm of approximate k-nearest neighbors query has shown that trading quality for time can be widely profitable in that context. In this paper, we introduce a new approximate search paradigm, called Statistical Similarity Search (S3 ), dedicated to local fingerprints and we describe the original indexing structure we hav...

• Type: Conference
• Year: 2005
• Where: ICDE
• Authors: Alexis Joly, Olivier Buisson, Carl Frélicot
• Keywords: Approximate Search, Approximate Search Paradigm, Database, ICDE 2005, Local fingerprints