Searching for near-duplicate video sequences from a scalable sequence aligner

Abstract : Near-duplicate video sequence identification consists in identifying real positions of a specific video clip in a video stream stored in a database. To address this problem, we propose a new approach based on a scalable sequence aligner borrowed from proteomics. Sequence alignment is performed on symbolic representations of features extracted from the input videos, based on an algorithm originally applied to bio-informatics. Experimental results demonstrate that our method performance achieved 94% recall with 100% precision, with an average searching time of about 1 second.
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Submitted on : Tuesday, November 19, 2013 - 3:24:31 PM
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  • HAL Id : hal-00906327, version 1


Leonardo de Oliveira, Zenilton Kleber Do Patrocínio Jr., Silvio Jamil Guimarães, Guillaume Gravier. Searching for near-duplicate video sequences from a scalable sequence aligner. IEEE International Symposium on Multimedia, 2013, United States. pp.4. ⟨hal-00906327⟩



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