People Groping by Spatio-Temporal Features of Trajectories

This paper proposes a method for detecting people groups from their trajectory data. This grouping is applied to each pair of people. The trajectories of the pair are featured by their spatio-temporal relationships such as a distance and velocities. The features are classified to either of “group” or “non-group” by a discriminative classifier. In contrast to previous features, the proposed features are robust to unsteady behaviors of people and noise of their trajectories. Experimental results using a publicly-available dataset of trajectories demonstrate the effectiveness of the proposed method.

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