Motion-based video retrieval by trajectory matching

This paper proposes a hybrid motion-based video retrieval system to retrieve desired videos from video databases through trajectory matching. The hybrid method includes a sketch-based scheme and a string-based one to analyze and index a trajectory with more syntactic meanings. First of all, this method uses a sampling technique to extract a set of control points from each trajectory as features. Then, the sketch-based method uses a curve fitting technique to interpolate some missed data in this set of control points. Then, the visual distance between any two trajectories can be directly measured by comparing their position data. The visual distance is good in solving the problem of translation-invariant trajectory matching but poor in solving the problem of partial trajectory matching. Therefore, in addition to the visual distance, the hybrid method uses the string-based scheme to compare any two trajectories according to their syntactic meanings. With the help of the syntactic distance, many impossible candidates can be filtered out in advance and thus the accuracy of video retrieval can be much enhanced. In addition, the problem of partial trajectory matching will become easy to be solved. Thus, even though a partial trajectory is queried, all desired video clips still can be very accurately retrieved. Experimental results have proved the superiority of our proposed method.