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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2013  >  13(3): 113-120
SUN Shou-qun, LIU Kang-ya, LIU Shuo-yan, LU: Xiao-jun, ZHAN Xuan. Moving target detection in complex environment of railway station[J]. Journal of Traffic and Transportation Engineering, 2013, 13(3): 113-120. doi: 10.19818/j.cnki.1671-1637.2013.03.016
Citation: SUN Shou-qun, LIU Kang-ya, LIU Shuo-yan, LU: Xiao-jun, ZHAN Xuan. Moving target detection in complex environment of railway station[J]. Journal of Traffic and Transportation Engineering, 2013, 13(3): 113-120. doi: 10.19818/j.cnki.1671-1637.2013.03.016
shu

Moving target detection in complex environment of railway station

doi: 10.19818/j.cnki.1671-1637.2013.03.016
  • 1.

    School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

  • 2.

    Institute of Computing Technology, China Academy of Railway Sciences, Beijing 100081, China

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  • Author Bio:

    SUN Shourqun(1964-), male, associate professor, PhD, +86-21-55275056, jrssq@163.com

  • Received Date: 2013-01-18
  • Publish Date: 2013-06-25
    Abstract
  • Traditional GMM(Gaussian mixture model) was dived into background layer, completion layer and noise layer by using hierarchical organization.Diverse update mechanisms were applied in different layers. In order to correct possible misjudgment, promotion and downgraded mechanisms were introduced between layers. To eliminate noise, noise layer was updated by using noise filter based on contour detection. In order to improve the adaptability for changing background, pseudo foreground area was detected by using histogram matching. The detection effect of improved GMM was verified by using the videos of station and parking lot. Verification result indicates that the problem of long-term static target being merged into background is settled. The impact of light mutations or camera noise is reduced. The updating speed of model increases when the background changes. Detection speed increases by 10% compared with traditional GMM.The efficiency and accuracy of moving target detection in railway station are improved by improved GMM, and the foundation for intelligent video analysis is laid.

     

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