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Hung-Yu Yeh, I-Cheng Chang, Yung-Hsin Chen. An Event Alarm System Based on Single and Group Human Behavior Analysis[J]. Journal of Electronic Science and Technology, 2017, 15(2): 123-132. DOI: 10.11989/JEST.1674-862X.6062810
Citation: Hung-Yu Yeh, I-Cheng Chang, Yung-Hsin Chen. An Event Alarm System Based on Single and Group Human Behavior Analysis[J]. Journal of Electronic Science and Technology, 2017, 15(2): 123-132. DOI: 10.11989/JEST.1674-862X.6062810
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An Event Alarm System Based on Single and Group Human Behavior Analysis

doi: 10.11989/JEST.1674-862X.6062810
  • 1.

    the Department of Computer Science &Information Engineering,National Dong Hwa University,Hualien 97401;

  • 2.

    Cal-Comp Electronics and Communications Company Ltd.,Taipei 10571

Funds: 

This work was supported by the MOST under Grant No. 104-2221-E-259-024-MY2

More Information
  • Author Bio:

    Hung-Yu Yeh. His research interests include computer vision, machine learning, object detection, and human behavior analysis,e-mail:world4jason@divc;
    Yung-Hsin Chen. His research interests include image processing and human behavior analysis,e-mail:icchang@mail.ndhu.edu.tw

    Hung-Yu Yeh. His research interests include computer vision, machine learning, object detection, and human behavior analysis,e-mail:world4jason@divc;
    Yung-Hsin Chen. His research interests include image processing and human behavior analysis,e-mail:icchang@mail.ndhu.edu.tw

  • Received Date: 2016-06-27
  • Rev Recd Date: 2016-08-31
  • Publish Date: 2017-06-24
    Abstract
  • Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether or not the people need help in a public place. Different from previous work, our work considers not only the behaviors of the target person but also the interaction between him and nearby people. In the paper, we propose an event alarm system which can detect the human behaviors and recognize the happening event through integrating the results generated from the single and group behavior analysis. Several new effective features are proposed in the study. Besides, a mechanism capable of extracting one-to-one and multiple-to-one relations is also developed. Experimental results show that the proposed approach can correctly detect human behaviors and provide the alarm messages when emergency events occur.
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    • References(19)
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