Performance analysis of local indexing methods for video copy detection
Technological developments and increases of the copyright infringements have led a demand on developing automatic video copy detection systems. Generally, for this task, even if visual local descriptors are preferred, descriptors should be indexed according to make an effective search. In this work, performance of three indexing methods which are defined in literature is compared for video copy detection task. Additionally estimating geometric relation between video frames has positive effect on performance is shown. Evaluation of proposed methods are tested on TRECVID 2009 content based video copy detection dataset and from obtained results, product quantization method yields much more accurate result with respect to classical bag-of-word method is observed.