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.