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Gesture recognition based on modified adaptive orthogonal matching pursuit algorithm

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Abstract

Aiming at the disadvantages of greedy algorithms in sparse solution, a modified adaptive orthogonal matching pursuit algorithm (MAOMP) is proposed in this paper. It is obviously improved to introduce sparsity and variable step size for the MAOMP. The algorithm estimates the initial value of sparsity by matching test, and will decrease the number of subsequent iterations. Finally, the step size is adjusted to select atoms and approximate the true sparsity at different stages. The simulation results show that the algorithm which has proposed improves the recognition accuracy and efficiency comparing with other greedy algorithms.

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Acknowledgements

This work was supported by Grants of National Natural Science Foundation of China (Grant Nos. 51575407, 51575338, 61273106, 51575412).

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Authors and Affiliations

  1. Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, 430081, China

    Bei Li, Ying Sun, Gongfa Li, Jianyi Kong, Guozhang Jiang, Bo Tao & Shuang Xu

  2. Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China

    Ying Sun, Gongfa Li, Jianyi Kong, Guozhang Jiang, Du Jiang, Bo Tao & Shuang Xu

  3. School of Computing, University of Portsmouth, Portsmouth, PO1 3HE, UK

    Honghai Liu

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  1. Bei Li
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Correspondence to Gongfa Li.

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Li, B., Sun, Y., Li, G. et al. Gesture recognition based on modified adaptive orthogonal matching pursuit algorithm. Cluster Comput 22 (Suppl 1), 503–512 (2019). https://doi.org/10.1007/s10586-017-1231-7

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  • DOI: https://doi.org/10.1007/s10586-017-1231-7

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