Effective real-scenario Video Copy Detection

Abstract

our task of video copy detection system aims to locate vicdeo segments that are partially copied or near-duplicated versions from an archive of reference videos. In 2010, video copy detection problem was sometimes considered as a solved problem, since previous research within this area used either small-scale or large-scale datasets (e.g. TRECVID 2009, Muscle-VCD) with pre-defined simulated videos. Therefore, the near-perfect results obtained on these datasets were somehow not convincing. As a result, in this paper, we introduce an effective real-scenario video copy detection system which aims to effectively and efficiently detect complex real video copies. Our system obtains decent results on a real-scenario large-scale video copy database (VCDB) generated in 2014, and measures the trade-off between effectiveness and efficiency. We believe our work can be regarded as the beginning for this challenging problem.