Chinese Journal of Lasers, Volume. 41, Issue 11, 1109002(2014)

Moving Object Detection Based on Improved Single Gaussian Background Model

Chen Yin*, Ren Kan, Gu Guohua, Qian Weixian, and Xu Fuyuan
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  • [in Chinese]
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    Aiming at the non-adaptive problem and incomplete detection of single Gaussian background model (SGM), an improved single Gaussian background model method for moving object detecton is proposed. This method combines SGM and the mean shift algorithm to detect moving objects. The initial background model is decided by using N frames of images, and the moving objects are detected, the pixel which belong to background points are updated according to the single Gaussian model algorithm, and the pixel which do not belong to the background points in the updated background model are corrected using the mean shift algorithm, the background model corrected by the mean shift algorithm is used as the final background model. The moving objects are detected using the background difference method. The experiments show that the improved method can overcome the non-adaptive shortcoming and have high detectivity.

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    Chen Yin, Ren Kan, Gu Guohua, Qian Weixian, Xu Fuyuan. Moving Object Detection Based on Improved Single Gaussian Background Model[J]. Chinese Journal of Lasers, 2014, 41(11): 1109002

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    Paper Information

    Category: holography and information processing

    Received: May. 20, 2014

    Accepted: --

    Published Online: Oct. 8, 2014

    The Author Email: Yin Chen (cy08042402@163.com)

    DOI:10.3788/cjl201441.1109002

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