Babaz: a large scale audio search system for video copy detection

Hervé Jégou 1 Jonathan Delhumeau 1 Jiangbo Yuan 1, 2 Guillaume Gravier 1 Patrick Gros 1
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper presents Babaz, an audio search system to search modified segments in large databases of music or video tracks. It is based on an efficient audio feature matching system which exploits the reciprocal nearest neighbors to produce a per-match similarity score. Temporal consistency is taken into account based on the audio matches, and boundary estimation allows the precise localization of the matching segments. The method is mainly intended for video retrieval based on their audio track, as typically evaluated in the copy detection task of Trecvid evaluation campaigns. The evaluation conducted on music retrieval shows that our system is comparable to a reference audio fingerprinting system for music retrieval, and significantly outperforms it on audio-based video retrieval, as shown by our experiments conducted on the dataset used in the copy detection task of Trecvid'2010 campaign.
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Submitted on : Friday, January 20, 2012 - 10:15:58 AM
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Hervé Jégou, Jonathan Delhumeau, Jiangbo Yuan, Guillaume Gravier, Patrick Gros. Babaz: a large scale audio search system for video copy detection. ICASSP - 37th International Conference on Acoustics, Speech, and Signal Processing, Mar 2012, Kyoto, Japan. ⟨hal-00661581⟩

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