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Spatio-Temporal Signatures for Video Copy Detection

Abstract : The number of copied videos is growing rapidly on television broadcast networks as well as on the world wide web. The existing copy detection methods resort either to image techniques or to video ones. We propose a spatio-temporal signature for the automatic detection of video extracts, based on the evolution of gray level centroids along time. We have obtained good results for a base of more than 50 Gb of data and for numerous tests of robustness. Our algorithm is robust to changes in contrast and brightness, zooms, modification of frame rate, a logo superimposition on the image, etc.
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Submitted on : Thursday, September 7, 2017 - 10:42:58 AM
Last modification on : Thursday, November 21, 2019 - 2:21:48 AM


  • HAL Id : hal-01583286, version 1


Isabelle Simand, Denis Pellerin, Stéphane Bres, Jean-Michel Jolion. Spatio-Temporal Signatures for Video Copy Detection. ACIVS 2004, Jan 2004, Bruxelle, Belgium. pp.421-427. ⟨hal-01583286⟩



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