The recognition of stop point in trajectory is the key step to transform spatial trajectory into semantic trajectory. At present, the recognition method of the stop point lacks the consideration of the time continuity of the record point, which leads to the lack of time information of the identified stop point. At the same time, in the scenario of missing track points, the information of stop point cannot be accurately identified. In order to solve these problems, this study proposes a velocity based spatio-temporal clustering method. Firstly, the real missing sub trajectories are determined by the spatio-temporal characteristics of the missing trajectories, and then the missing trajectories are interpolated according to the average velocity of the missing trajectories. In the experiment, GeoLife trajectory data is used to verify the proposed method. The results show that the algorithm can effectively identify the user's stop point, and has relatively sound robustness to the interference in the trajectory.