Acta Optica Sinica, Volume. 39, Issue 8, 0815003(2019)

Multi-Feature Background Modeling Algorithm Based on Improved Census Transform

Zhicheng Guo1,2, Jianwu Dang1,2、*, Yangping Wang1,2, and Jing Jin1,2
Author Affiliations
  • 1 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • 2 Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, Lanzhou, Gansu 730070, China;
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    References(17)

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    [13] Stein F. Efficient computation of optical flow using the census transform[M]. ∥Rasmussen C E, Bülthoff H H, Schölkopf B, et al. Pattern recognition. Lecture notes in computer science. Berlin, Heidelberg: Springer, 3175, 79-86(2004).

    [16] Liao S C, Zhao G Y, Kellokumpu V et al. Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes. [C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 1301-1306(2010).

    [17] Wang Y, Jodoin P M, Porikli F et al. CDnet 2014: an expanded change detection benchmark dataset. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 393-400(2014).

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    Zhicheng Guo, Jianwu Dang, Yangping Wang, Jing Jin. Multi-Feature Background Modeling Algorithm Based on Improved Census Transform[J]. Acta Optica Sinica, 2019, 39(8): 0815003

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    Paper Information

    Category: Machine Vision

    Received: Mar. 6, 2019

    Accepted: Apr. 8, 2019

    Published Online: Aug. 7, 2019

    The Author Email: Jianwu Dang (lzjdgr@163.com)

    DOI:10.3788/AOS201939.0815003

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