INRIA LEAR-TEXMEX: Video copy detection task

Hervé Jégou 1 Matthijs Douze 2 Guillaume Gravier 3 Cordelia Schmid 2 Patrick Gros 1
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
2 LEAR - Learning and recognition in vision
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
3 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this paper we present the results of our experiments in the Trecvid'10 copy detection task and introduce the components of our system. In particular, we describe the recent approximate nearest neighbor search method we used to index the hundreds millions of audio descriptors. Our system obtained excellent accuracy and localization results, achieving the best performance on a few transformations, and this with a single kind of image descriptor. Moreover, the analysis evidences that our system can be significantly improved.
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Submitted on : Wednesday, February 9, 2011 - 11:46:24 AM
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Hervé Jégou, Matthijs Douze, Guillaume Gravier, Cordelia Schmid, Patrick Gros. INRIA LEAR-TEXMEX: Video copy detection task. TRECVid 2010 Workshop, Nov 2010, Gaithersburg, United States. ⟨inria-00555825⟩

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