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Association Strategy Graph Convolutional Neural Network for Human Skeletal Behavior Recognition

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Data Science (ICPCSEE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1628))

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Abstract

Aiming at the problem that the joint point partition strategy expresses the important information of the human body in the human body behavior recognition of bones cannot fully express the behavior, an RCTR-GCN human bone behavior recognition model of the correlation strategy is proposed. First, by adding an association strategy of a refined graph convolutional network model (CTR-GCN) of the smart channel topology, it can dynamically learn different topological structures and efficiently amplify the characteristics of the connection points in different channels while improving the key joint points of associated characteristics. Then, the network model redefines each channel by learning a shared topology and uses a specific channel relationship to unify the model through theoretical analysis; finally, redefining the model structure effectively reflects the associated information of local nodes within the channel. Action recognition has stronger aggregation capabilities. The results show that the recognition accuracy in the commonly used NTU RGB + D and NW-UCLA datasets reaches 93.6% (X-View), 97.6% (X-Sub), and 97.2%, respectively. The experimental results show that the accuracy rate is improved.

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Authors and Affiliations

  1. Center for Information Technology, Dalian Polytechnic University, Dalian, 116034, Liaoning, China

    Tinglong Liu

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  1. Tinglong Liu
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Correspondence to Tinglong Liu .

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Editors and Affiliations

  1. Southwest Petroleum University, Chengdu, China

    Yang Wang

  2. University of Electronic Science and Technology of China, Chengdu, China

    Guobin Zhu

  3. Harbin Engineering University, Harbin, China

    Qilong Han

  4. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang

  5. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  6. National Academy of Guo Ding Institute of Data Sciences, Beijing, China

    Zeguang Lu

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Liu, T. (2022). Association Strategy Graph Convolutional Neural Network for Human Skeletal Behavior Recognition. In: Wang, Y., Zhu, G., Han, Q., Wang, H., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2022. Communications in Computer and Information Science, vol 1628. Springer, Singapore. https://doi.org/10.1007/978-981-19-5194-7_30

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  • DOI: https://doi.org/10.1007/978-981-19-5194-7_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-5193-0

  • Online ISBN: 978-981-19-5194-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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