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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2018> 27(1): 51-57
Zheyi Fan, Shuqin Weng, Jiao Jiang, Yixuan Zhu, Zhiwen Liu. Particle Filter Object Tracking Algorithm Based on Sparse Representation and Nonlinear Resampling[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2018, 27(1): 51-57. doi: 10.15918/j.jbit1004-0579.201827.0107
Citation: Zheyi Fan, Shuqin Weng, Jiao Jiang, Yixuan Zhu, Zhiwen Liu. Particle Filter Object Tracking Algorithm Based on Sparse Representation and Nonlinear Resampling[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2018, 27(1): 51-57.doi:10.15918/j.jbit1004-0579.201827.0107
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Particle Filter Object Tracking Algorithm Based on Sparse Representation and Nonlinear Resampling

doi:10.15918/j.jbit1004-0579.201827.0107

  • School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

  • Received Date:2017-03-27
    Abstract
  • Object tracking with abrupt motion is an important research topic and has attracted wide attention. To obtain accurate tracking results, an improved particle filter tracking algorithm based on sparse representation and nonlinear resampling is proposed in this paper. First, the sparse representation is used to compute particle weights by considering the fact that the weights are sparse when the object moves abruptly, so the potential object region can be predicted more precisely. Then, a nonlinear resampling process is proposed by utilizing the nonlinear sorting strategy, which can solve the problem of particle diversity impoverishment caused by traditional resampling methods. Experimental results based on videos containing objects with various abrupt motions have demonstrated the effectiveness of the proposed algorithm.
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    • References (13)
  • [1]
    Li M, Fan Z Y, Liu Z W. An improved visual tracking algorithm based on particle filter[C]//2013 IEEE International Conference of IEEE Region 10, Xi'an, Shaanxi, China, 2013:1-4.
    [2]
    Cai Z W, Wen L Y, Lei Z, et al. Robust deformable and occluded object tracking with dynamic graph[J]. IEEE Transaction on Image Processing, 2014, 23(12):5497-5509.
    [3]
    Kwon J, Lee K M. Tracking by sampling and integrating multiple trackers[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(7):1428-1441.
    [4]
    Kwon J, Lee K M. Wang-Landau Monte Carlo-based tracking methods for abrupt motions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013,35(4):1011-1024.
    [5]
    Nguyen T, Pridmore T P. Tracking using multiple linear searches and motion direction sampling[C]//201422nd International Conference on Pattern Recognition, Stockholm, Sweden, 2014:2191-2196.
    [6]
    Zhou X, Lu Y. Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling[C]//2010 IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010:1847-1854.
    [7]
    Doucet A, Gordon N J. Sequential monte carlo methods in practice[M]. Berlin,Germany:Springer, 2001.
    [8]
    Su Y, Zhao Q, Zhao L, et al. Abrupt motion tracking using a visual saliency embedded particle filter[J]. Pattern Recognition, 2014, 47(5):18261834.
    [9]
    Morimitsu H, Bloch I. Attributed graphs for tracking multiple objects in structured sports videos[C]//Proceedings of the IEEE International Conference on Computer Vision Workshops, Santiago, Chile, 2015:34-42.
    [10]
    Choi H D, Ahn C K, Lim M T. Gaussian distribution resampling algorithm of particle filter[C]//Proceedings of the International Conference on Control, Automation and Systems, Gwangju, Korea, 2013.
    [11]
    Li Mo, Yin Licheng, Yan Tianyi. Particle filter tracking algorithm based on integral histogram and improved resampling[J]. Optics and Electronic Technology, 2013, 11(3):45-48. (in Chinese)
    [12]
    Yu J X, Liu W J, Tang Y L. Improved particle filter algorithms based on partial systematic resampling[C]//2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, Xiamen, China, 2010:483-487.
    [13]
    Birchfield S. Elliptical head tracking using intensity gradients andcolor histograms[C]//1998 IEEE Computer Society Conferenceon Computer Vision and Pattern Recognition, Santa Barbara, CA, USA, 1998:232-237.
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