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ZTE Communications ›› 2017, Vol. 15 ›› Issue (1): 55-60.DOI: 10.3969/j.issn.1673-5188.2017.01.009

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  • 收稿日期:2015-11-16 出版日期:2017-02-25 发布日期:2019-12-24

Moving Target Detection and Tracking for Smartphone Automatic Focusing

HU Rongchun, WANG Xiaoyang, ZHENG Yunchang, PENG Zhenming   

  1. School of Opto-Electronic Information, University of Electronic Science and Technology of China, Chengdu 610051, China
  • Received:2015-11-16 Online:2017-02-25 Published:2019-12-24
  • About author:HU Rongchun (hrc@swust.edu.cn) received his master’s degree in information and communication engineering from University of Science and Technology of China (UESTC) in 2007. He is a lecture and pursuing the Ph.D. degree in signal and information processing at UESTC. His research interests include machine learning and image processing.|WANG Xiaoyang (xywang_2012@163.com) received her B.E. degree in electronic science and technology from University of Electronic Science and Technology of China. She is currently a Ph.D. candidate in signal and information processing there. Her research interests include image processing, computer vision, and compressive sensing theory and applications.|ZHENG Yunchang (zhengyunchang@foxmail.com) received the B.E. and M.S. degrees in electronic science and technology from University of Electronic Science and Technology of China. His research interests include machine learning and computer vision.|PENG Zhenming (zmpeng@uestc.edu.cn) received his Ph.D. degree in geo-detection and information technology from Chengdu University of Technology, China in 2001. From 2001 to 2003, he was a postdoctoral researcher with the Institute of Optics and Electronics (IOE), Chinese Academy of Sciences. He is a professor with University of Electronic Science and Technology of China. His research interests include image processing, radar signal processing, and target recognition and tracking. Prof. PENG is a member of the IEEE and the Aerospace Society of China.
  • Supported by:
    This work was supported by ZTE Industry-Academia-Research Cooperation Funds

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Abstract:

In this paper, a non-contact auto-focusing method is proposed for the essential function of auto-focusing in mobile devices. Firstly, we introduce an effective target detection method combining the 3-frame difference algorithm and Gauss mixture model, which is robust for complex and changing background. Secondly, a stable tracking method is proposed using the local binary patter feature and camshift tracker. Auto-focusing is achieved by using the coordinate obtained during the detection and tracking procedure. Experiments show that the proposed method can deal with complex and changing background. When there exist multiple moving objects, the proposed method also has good detection and tracking performance. The proposed method implements high efficiency, which means it can be easily used in real mobile device systems.

Key words: moving target detection, frame-difference method, background modeling method, camshift tracking, meanshift tracking, auto-focusing