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Title of Journal: J Cent South Univ

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Abbravation: Journal of Central South University

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Springer Berlin Heidelberg

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DOI

10.1016/0047-2484(79)90057-5

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2227-5223

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Human action recognition based on chaotic invarian

Authors: Liming Xia Jinxia Huang Lunzheng Tan
Publish Date: 2013/11/13
Volume: 20, Issue: 11, Pages: 3171-3179
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Abstract

A new human action recognition approach was presented based on chaotic invariants and relevance vector machines RVM The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action The CC method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory Then some chaotic invariants representing action can be captured in the reconstructed phase space Finally RVM was used to recognize action Experiments were performed on the KTH Weizmann and Ballet human action datasets to test and evaluate the proposed method The experiment results show that the average recognition accuracy is over 912 which validates its effectiveness

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