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In this paper, we propose a robust technique for temporal alignment of video sequences with similar planar motions acquired using uncalibrated cameras. In this technique, we model the motion-based video temporal alignment problem as a spatio-temporal discrete trajectory point sets alignment problem. First, the trajectory of the object of interest is tracked throughout the videos. A probabilistic method is then developed to calculate the `soft' spatial correspondence between the trajectory point sets. Next, a dynamic time warping technique (DTW) is applied to the spatial correspondence information to compute the temporal alignment of the videos. The experimental results show that the proposed technique provides a superior performance over existing techniques for videos with similar trajectory patterns.