Laser & Optoelectronics Progress, Volume. 58, Issue 8, 0815008(2021)

Video Foreground-Background Separation via Weighted Schatten-p Norm and Structured Sparsity Decomposition

Yufeng Wei1, Mingli Jing1、*, Lan Li2, Kun Sun1, and Ruibo Fan1
Author Affiliations
  • 1School of Electronic Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China
  • 2School of Science, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China
  • show less
    References(25)

    [9] Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 52, 1289-1306(2006).

    [11] Candès E J, Tao T. Near-optimal signal recovery from random projections: universal encoding strategies?[J]. IEEE Transactions on Information Theory, 52, 5406-5425(2006).

    [12] Candès E J, Li X, Ma Y et al. Robust principal component analysis[J]. Journal of the ACM, 58, 1-37(2011).

    [13] Wright J, Ganesh A, Rao S et al. Robust principal component analysis: exact recovery of corrupted low-rank matrices[C]. // Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems, December 7-10, 2009, Vancouver, British Columbia, Canada. New York: NIPS, 2080-2088(2009).

    [14] Zhou T Y, Tao D C. GoDec: randomized low-rank & sparse matrix decomposition in noisy case[C]. //Proceedings of 2011 International Conference on International Conference on Machine Learning, June 28-July 28, 2011, Bellevue, Washington, United States. New Jersey: IMLS, 978, 33-40(2011).

    [16] Zhang D B, Hu Y, Ye J P et al. Matrix completion by truncated nuclear norm regularization[C]. //2012 IEEE Conference on Computer Vision and Pattern Recognition, June 16-21, 2012, Providence, RI, USA., 2192-2199(2012).

    [17] Nie F P, Huang H, Ding C. Low-rank matrix recovery via efficient Schatten p-norm minimization[J]. Proceedings of the National Conference on Artificial Intelligence, 1, 655-661(2012).

    [18] Xie Y, Gu S H, Liu Y et al. Weighted Schatten p-norm minimization for image denoising and background subtraction[J]. IEEE Transactions on Image Processing, 25, 4842-4857(2016).

    [19] Guyon C, Bouwmans T, Zahzah E H. Foreground detection based on low-rank and block-sparse matrix decomposition[C]. //2012 19th IEEE International Conference on Image Processing, September 30-October 3, 2012, Orlando, FL, USA., 1225-1228(2012).

    [21] Zuo W M, Meng D Y, Zhang L et al. A generalized iterated shrinkage algorithm for non-convex sparse coding[C]. //2013 IEEE International Conference on Computer Vision, December 1-8, 2013, Sydney, NSW, Australia., 217-224(2013).

    [22] Mairal J, Jenatton R, Bach F et al. Network flow algorithms for structured sparsity[C]. //Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, December 6-9, 2010, Vancouver, British Columbia, Canada. New York: NIPS, 1558-1566(2010).

    [24] 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, 393-400(2014).

    [25] Toyama K, Krumm J, Brumitt B et al. Wallflower: principles and practice of background maintenance[C]. //Proceedings of the Seventh IEEE International Conference on Computer Vision, September 20-27, 1999, Kerkyra, Greece, 255-261(1999).

    Tools

    Get Citation

    Copy Citation Text

    Yufeng Wei, Mingli Jing, Lan Li, Kun Sun, Ruibo Fan. Video Foreground-Background Separation via Weighted Schatten-p Norm and Structured Sparsity Decomposition[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0815008

    Download Citation

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

    Category: Machine Vision

    Received: Sep. 30, 2020

    Accepted: Nov. 5, 2020

    Published Online: Apr. 16, 2021

    The Author Email: Jing Mingli (mljingsy@xsyu.edu.cn)

    DOI:10.3788/LOP202158.0815008

    Topics