Motion is one of the most prominent features of video. For content-based video retrieval, motion trajectory is the intuitive specification of motion features. In this paper, approaches for video retrieval via single motion trajectory and multiple motion trajectories are addressed. For the retrieval via single motion trajectory, the trajectory is modeled as a sequence of segments and each segment is represented as the slope. Two quantitative similarity measures and corresponding algorithms based on the sequence similarity are presented. For the retrieval via multiple motion trajectories, the trajectories of the video are modeled as a sequence of symbolic pictures. Four quantitative similarity measures and algorithms, which are also based on the sequence similarity, are proposed. All the proposed algorithms are developed based on the dynamic programming approach.