Video Copy Detection providing Localized Matches

Damian Borth, Adrian Ulges, Christian Schulze, Thomas Breuel
GI-Informatiktage 2009, Bonn, Germany, Gesellschaft für Informatik e.V., 2/2009


With the availability of large scale online video platforms like YouTube, copyright infringement becomes a severe problem, such that the demand for robust copy detection systems is growing. Such system must find multiple occurrence of copyright protected material within video clips that are created, modified, remixed and uploaded by the user. A particular challenge is to find the exact position of a copy in a "potentially huge" reference database. For this purpose, this paper presents a Content Based Copy Detection system that both detects copies in query videos against a reference database and gives an exact alignment between them. For finding and aligning a matching shot, a fast search for candidates is conducted, and as a second step an exact alignment is found using a dynamic programming minimization of the well-known edit distance from text retrieval. The introduced approach was evaluated on the public available MUSCLE-VCD-2007 data corpus and showed competitive alignment results compared to the ACM CVPR 2007 evaluation.




@inproceedings{ BORT2009,
	Title = {Video Copy Detection providing Localized Matches},
	Author = {Damian Borth and Adrian Ulges and Christian Schulze and Thomas Breuel},
	BookTitle = {GI-Informatiktage 2009},
	Month = {2},
	Year = {2009},
	Publisher = {Gesellschaft für Informatik e.V.}

Last modified:: 30.08.2016