IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Trajectory-Set Feature for Action Recognition
Kenji MATSUIToru TAMAKIBisser RAYTCHEVKazufumi KANEDA
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JOURNAL FREE ACCESS

2017 Volume E100.D Issue 8 Pages 1922-1924

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Abstract

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 action dataset demonstrates that TS is comparable to state-of-the-arts, and outperforms iDT; the accuracy of 95.0%, compared to 91.7% by iDT.

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© 2017 The Institute of Electronics, Information and Communication Engineers
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