Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories

11/28/2017

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by   Kenji Matsui, et al.

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We propose a feature for action recognition called Trajectory-Set (TS), on top of the improved Dense Trajectory (iDT). The TS feature encodes only trajectories around densely sampled interest points, without any appearance features. Experimental results on the UCF50, UCF101, and HMDB51 action datasets demonstrate that TS is comparable to state-of-the-arts, and outperforms many other methods; for HMDB the accuracy of 85.4 80.2 https://github.com/Gauffret/TrajectorySet .