Abstract
A novel human body action recognition method based on Kinect is proposed. Firstly, the key frame of the original data is extracted by using the key frame extraction technology based on quaternion. Secondly, the moving pose feature based on the motion information of each joint point is constituted for the skeleton information of each key frame. And, combined with key frame, online continuous action segmentation is implemented by using boundary detection method. Finally, the feature is encoded by Fisher vector and input to the linear SVM classifier to complete the action recognition. In the public dataset MSR Action3D and the dataset collected in this paper, the experiments show that the proposed method achieves a good recognition effect.
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Acknowledgments
This paper is supported by the Guangxi Natural Science Foundation Project (2014GXNSFAA118395), the research project of Guangxi Colleges & Universities Key Laboratory of Intelligent Processing of Image and Graphics (GIIP201706), the National Natural Science Foundation Project (61763007), the key project of the Guangxi Natural Science Foundation (2017GXNSFDA198028).
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Yin, D., Miao, YQ., Qiu, K., Wang, A. (2018). Study on Human Body Action Recognition. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_10
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