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An image-based approach to video copy detection with spatio-temporal post-filtering

Matthijs Douze 1, 2 Hervé Jégou 3 Cordelia Schmid 1 
1 LEAR - Learning and recognition in vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
3 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper introduces a video copy detection system which efficiently matches individual frames and then verifies their spatio-temporal consistency. The approach for matching frames relies on a recent local feature indexing method, which is at the same time robust to significant video transformations and efficient in terms of memory usage and computation time. We match either keyframes or uniformly sampled frames. To further improve the results, a verification step robustly estimates a spatio-temporal model between the query video and the potentially corresponding video segments. Experimental results evaluate the different parameters of our system and measure the trade-off between accuracy and efficiency. We show that our system obtains excellent results for the TRECVID 2008 copy detection task.
Keywords : video search TRECVID
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Submitted on : Tuesday, June 28, 2011 - 1:21:56 AM
Last modification on : Thursday, January 20, 2022 - 5:28:07 PM
Long-term archiving on: : Monday, November 12, 2012 - 9:45:38 AM


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Matthijs Douze, Hervé Jégou, Cordelia Schmid. An image-based approach to video copy detection with spatio-temporal post-filtering. IEEE Transactions on Multimedia, 2010, 12 (4), pp.257-266. ⟨10.1109/TMM.2010.2046265⟩. ⟨inria-00604034⟩



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