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We propose in this paper an architecture for near-duplicate video detectionbased on: (i) index and query signature based structures integrating temporaland perceptual visual features and (ii) a matching framework computing thelogical inference between index and query documents. As far as indexing isconcerned, instead of concatenating low-level visual features inhigh-dimensional spaces which results in curse of dimensionality and redundancyissues, we adopt a perceptual symbolic representation based on color andtexture concepts. For matching, we propose to instantiate a retrieval modelbased on logical inference through the coupling of an N-gram sliding windowprocess and theoretically-sound lattice-based structures. The techniques wecover are robust and insensitive to general video editing and/or degradation,making it ideal for re-broadcasted video search. Experiments are carried out onlarge quantities of video data collected from the TRECVID 02, 03 and 04collections and real-world video broadcasts recorded from two German TVstations. An empirical comparison over two state-of-the-art dynamic programmingtechniques is encouraging and demonstrates the advantage and feasibility of ourmethod.

Near-duplicate video detection featuring coupled temporal and perceptual visual structures and logical inference based matching