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Cluster Computing

, Volume 22, Supplement 1, pp 503–512 | Cite as

Gesture recognition based on modified adaptive orthogonal matching pursuit algorithm

  • Bei Li
  • Ying Sun
  • Gongfa LiEmail author
  • Jianyi Kong
  • Guozhang Jiang
  • Du Jiang
  • Bo Tao
  • Shuang Xu
  • Honghai Liu
Article

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.

Keywords

Pursuit algorithm Gesture recognition Pattern recognition Sparse representation Estimation 

Notes

Acknowledgements

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

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Bei Li
    • 1
  • Ying Sun
    • 1
    • 2
  • Gongfa Li
    • 1
    • 2
    Email author
  • Jianyi Kong
    • 1
    • 2
  • Guozhang Jiang
    • 1
    • 2
  • Du Jiang
    • 2
  • Bo Tao
    • 1
    • 2
  • Shuang Xu
    • 1
    • 2
  • Honghai Liu
    • 3
  1. 1.Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of EducationWuhan University of Science and TechnologyWuhanChina
  2. 2.Hubei Key Laboratory of Mechanical Transmission and Manufacturing EngineeringWuhan University of Science and TechnologyWuhanChina
  3. 3.School of ComputingUniversity of PortsmouthPortsmouthUK

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