Enhanced spatio-temporal video copy detection by combining trajectory and spatial consistency

The recent improvements on internet technologies and video coding techniques cause an increase in copyright infringements especially for video. Frequently, image-based approaches appear as an essential solution due to the fact that joint usage of quantization-based indexing and weak geometric consistency stages give a capability to compare duplicate videos quickly. However, exploiting purely spatial content ignores the temporal variation of video. In this work, we propose a system that combines the state-of-the-art quantization-based indexing scheme with a novel trajectory-based geometric consistency on spatio-temporal features. This combination improves duplicate video matching task significantly. Briefly, spatial mean and variance of the trajectories are incorporated to establish a weak geometric consistency among pair of frames. To show the success of the proposed method, content-based video copy detection field is selected and TRECVID 2009 dataset is utilized. The experimental results show that constituting trajectory-based consistency on corresponding feature pairs outperforms the performances of merely utilizing spatiotemporal signature and visual signature with enhanced weak geometric consistency.