Hierarchical Human Action Recognition with Self-Selection Classifiers via Skeleton Data

Ben-Yue Su, Huang Wu, Min Sheng, Chuan-Sheng Shen

doi:10.1088/0253-6102/70/5/633

Communications in Theoretical Physics >

2018 , Vol. 70 >Issue 05: 633 - 640

DOI: https://doi.org/10.1088/0253-6102/70/5/633

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Hierarchical Human Action Recognition with Self-Selection Classifiers via Skeleton Data

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1. School of Computer and Information, Anqing Normal University, Anqing 246133, China;
2. The Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing 246133, China;
3. School of Mathematics and Computational Science, Anqing Normal University, Anqing 246133, China

Received date: 2018-04-30

Revised date: 2018-07-16

Online published: 2018-11-01

Supported by

Supported by the National Nature Science Foundation of China under Grant Nos. 11475003, 61603003, and 11471093; the Key Project of Cultivation of Leading Talents in Universities of Anhui Province under Grant No. gxfxZD2016174; Funds of Integration of Cloud Computing and Big Data; Innovation of Science and Technology of Ministry of Education of China under Grant No. 2017A09116; and Anhui Provincial Department of Education Outstanding Top-Notch Talent-Funded Project under Grant No. gxbjZD26

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Abstract

Human action recognition has become one of the most active research topics in human-computer interaction and artificial intelligence, and has attracted much attention. Here, we employ a low-cost optical sensor Kinect to capture the action information of the human skeleton. We then propose a two-level hierarchical human action recognition model with self-selection classifiers via skeleton data. Especially different optimal classifiers are selected by probability voting mechanism and 10 times 10-fold cross validation at different coarse grained levels. Extensive simulations on a well-known open dataset and results demonstrate that our proposed method is efficient in human action recognition, achieving 94.19% the average recognition rate and 95.61% the best rate.

Key words： human action recognition; hierarchical architecture model; self-selection classifiers; optimal classification unit

Cite this article

Ben-Yue Su, Huang Wu, Min Sheng, Chuan-Sheng Shen . Hierarchical Human Action Recognition with Self-Selection Classifiers via Skeleton Data[J]. Communications in Theoretical Physics, 2018 , 70(05) : 633 -640 . DOI: 10.1088/0253-6102/70/5/633

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