Speeding up complex video copy detection queries

Authors:
Ira Assent;Hardy Kremer;Thomas Seidl
Affiliations:
Department of Computer Science, Aalborg University, Denmark;Data management and exploration group, RWTH Aachen University, Germany;Data management and exploration group, RWTH Aachen University, Germany
Venue:
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Year:
2010

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Abstract

Massive amounts of video data from digital tv channels, online video communities, peer-to-peer networks, and video blogs require automated techniques for copyright enforcement and usage tracking. Effective video copy distortion models usually incur high computational cost. We propose an index supported multistep filter-and-refine algorithm for a complex copy detection model. We characterize a class of filters for which we prove completeness of the result, and provide further runtime improvement by a novel tight approximation. In thorough experiments, we demonstrate that our algorithm substantially improves processing times.