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Using Hidden Markov Model to Predict Human Actions with Swarm Intelligence

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10637))

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Abstract

This paper proposed a novel algorithm which named Randomized Particle Swarm Optimization (RPSO) to optimize HMM for human activity prediction. The experiments designed in this paper are the classification of human activity using two data sets. The first testing data is from the TUM Kitchen Data Set and the other is the Human Activity Recognition using the Smartphone Data Set from UCI Machine Learning Repository. Based on the comparison of the accuracies for the conventional HMM and optimized HMM, a conclusion can be drawn that the proposed RPSO can help HMM to achieve higher accuracy for human action recognition. Our results show that RPSO-HMM can improve 15% accuracy in human activity recognition and prediction when compared to the traditional HMM.

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Author information

Authors and Affiliations

  1. School of Information Technologies, The University of Sydney, Sydney, NSW, 2006, Australia

    Zhicheng Lu, Yuk Ying Chung, Henry Wing Fung Yeung & Seid Miad Zandavi

  2. Department of Engineering Science, University of Auckland, Auckland, New Zealand, 1010

    Weiming Zhi

  3. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, P.O. Box 24-60, Hsinchu, 300, Taiwan, Republic of China

    Wei-Chang Yeh

Authors
  1. Zhicheng Lu
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  2. Yuk Ying Chung
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  3. Henry Wing Fung Yeung
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  4. Seid Miad Zandavi
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  5. Weiming Zhi
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  6. Wei-Chang Yeh
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Corresponding author

Correspondence to Zhicheng Lu .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Lu, Z., Chung, Y.Y., Yeung, H.W.F., Zandavi, S.M., Zhi, W., Yeh, WC. (2017). Using Hidden Markov Model to Predict Human Actions with Swarm Intelligence. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10637. Springer, Cham. https://doi.org/10.1007/978-3-319-70093-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-70093-9_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70092-2

  • Online ISBN: 978-3-319-70093-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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