Laser & Optoelectronics Progress, Volume. 60, Issue 4, 0410010(2023)

Moving Object Detection Based on Nonconvex Rank Approximation and Three-Dimensional Total Variation

Yongli Wang, Xiaoyun Ding*, and Juliang Tao
Author Affiliations
  • College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
  • show less
    References(24)

    [1] Liu Z D, Dong L Q, Zhao Y J et al. Adaptive model tracking algorithm for fast-moving targets in video[J]. Acta Optica Sinica, 41, 1815001(2021).

    [2] Tang M N, Wang C Y. Moving object detection in static scene based on improved ViBe algorithm[J]. Laser & Optoelectronics Progress, 58, 1410011(2021).

    [3] Aufrichtig R, Wilson D L. X-ray fluoroscopy spatio-temporal filtering with object detection[J]. IEEE Transactions on Medical Imaging, 14, 733-746(1995).

    [4] Zhang L P, Fan H, Wang L Y et al. Research on moving object extraction by optical flow method[J]. Computer & Digital Engineering, 48, 83-87(2020).

    [5] Song H J, Shen M L. Target tracking algorithm based on optical flow method using corner detection[J]. Multimedia Tools and Applications, 52, 121-131(2011).

    [6] Kim W, Kim Y. Background subtraction using illumination-invariant structural complexity[J]. IEEE Signal Processing Letters, 23, 634-638(2016).

    [7] Zhang Y S, Zheng W B, Leng K J et al. Background subtraction using an adaptive local Median texture feature in illumination changes urban traffic scenes[J]. IEEE Access, 8, 130367-130378(2020).

    [8] Brenner E, Smeets J B J. Different frames of reference for position and motion[J]. Naturwissenschaften, 81, 30-32(1994).

    [9] Li N, Fan K G, Liu Y H et al. Unmanned aerial vehicle detection based on ASRPCA fused with five-frame difference[J]. Laser & Optoelectronics Progress, 58, 2015007(2021).

    [10] Candès E J, Wakin M B, Boyd S P. Enhancing sparsity by reweighted ℓ1 minimization[J]. Journal of Fourier Analysis and Applications, 14, 877-905(2008).

    [11] Oliver N M, Rosario B, Pentland A P. A Bayesian computer vision system for modeling human interactions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 831-843(2000).

    [12] Wright J, Ganesh A, Rao S et al. Robust principal component analysis: Exact recovery of corrupted low-rank matrices via convex optimization[C], 2080-2088(2009).

    [13] Wang Y L, Wei H C, Ding X Y et al. Video background/foreground separation model based on non-convex rank approximation RPCA and superpixel motion detection[J]. IEEE Access, 8, 157493-157503(2020).

    [14] Hu Y, Zhang D B, Ye J P et al. Fast and accurate matrix completion via truncated nuclear norm regularization[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 2117-2130(2013).

    [16] Chen Y Y. Study on matrix rank minimization algorithms and applications based on non-convex approximation[D](2017).

    [17] Cao X C, Yang L, Guo X J. Total variation regularized RPCA for irregularly moving object detection under dynamic background[J]. IEEE Transactions on Cybernetics, 46, 1014-1027(2016).

    [18] Hu Z X, Wang Y L, Su R et al. Moving object detection based on non-convex RPCA with segmentation constraint[J]. IEEE Access, 8, 41026-41036(2020).

    [19] Wang Y, Wei H, Ding X et al. Video Background/Foreground Separation Model Based on Non-Convex Rank Approximation RPCA and Superpixel Motion Detection[J]. IEEE Access, 1-1(2020).

    [20] Sun Z P, Wang Y L, Wang S Q et al. A new non-convex rank approximation RPCA model for video background separation[J]. Journal of Shandong University of Science and Technology (Natural Science), 38, 83-91(2019).

    [22] Gu S H, Zhang L, Zuo W M et al. Weighted nuclear norm minimization with application to image denoising[C], 2862-2869(2014).

    [23] Kang Z, Peng C, Cheng Q. Robust PCA via nonconvex rank approximation[C], 211-220(2015).

    [24] Xue Z C, Dong J, Zhao Y X et al. Low-rank and sparse matrix decomposition via the truncated nuclear norm and a sparse regularizer[J]. The Visual Computer, 35, 1549-1566(2019).

    Tools

    Get Citation

    Copy Citation Text

    Yongli Wang, Xiaoyun Ding, Juliang Tao. Moving Object Detection Based on Nonconvex Rank Approximation and Three-Dimensional Total Variation[J]. Laser & Optoelectronics Progress, 2023, 60(4): 0410010

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Nov. 17, 2021

    Accepted: Jan. 5, 2022

    Published Online: Feb. 13, 2023

    The Author Email: Ding Xiaoyun (dxy@sdust.edu.cn)

    DOI:10.3788/LOP212988

    Topics