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31 August 2018 Human action recognition using Kinect multimodal information
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Proceedings Volume 10835, Global Intelligence Industry Conference (GIIC 2018); 1083507 (2018) https://doi.org/10.1117/12.2505416
Event: Global Intelligent Industry Conference 2018, 2018, Beijing, China
Abstract
With the successful introduction and popularization of Kinect, it has been widely applied in intelligent surveillance, human-machine interaction and human action recognition and so on. This paper presents a human action recognition based on multimodal information using the Kinect sensor. Firstly, the HOG feature based on RGB modal information, the space-time interest points feature based on depth modal information, and the human body joints relative position feature based on skeleton modal information are extracted respectively for expressing human action. Then, the three kinds of nearest neighbor classifiers with different distance measurement formulas are used to predict the class label for a test sample which is respectively expressed by three different modal features. The experimental results show that the proposed method is simple, fast and efficient compared with other action recognition algorithms on public datasets.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chao Tang, Miao-hui Zhang, Xiao-feng Wang , Wei Li, Feng Cao, and Chun-ling Hu "Human action recognition using Kinect multimodal information", Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 1083507 (31 August 2018); https://doi.org/10.1117/12.2505416
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