• Laser & Optoelectronics Progress
  • Vol. 56, Issue 24, 241001 (2019)
Kaichuan Sun1, Chenhua Liu2、*, Guangshun Yao1, and Dawei Yang2
Author Affiliations
  • 1School of Computer and Information Engineering, Chuzhou University, Chuzhou, Anhui 239000, China
  • 2Shanghai Aerospace Control Technology Institute, Shanghai 201109, China
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    DOI: 10.3788/LOP56.241001 Cite this Article Set citation alerts
    Kaichuan Sun, Chenhua Liu, Guangshun Yao, Dawei Yang. Visual Tracking Combined Least Soft-Threshold Squares with Haar-like Feature Matching[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241001 Copy Citation Text show less
    References

    [1] Adam A, Rivlin E, Shimshoni I. Robust fragments-based tracking using the integral histogram. [C]∥2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06), June 17-22, 2006, New York, NY, USA. New York: IEEE(2006).

    [2] Ross D A, Lim J, Lin R S et al. Incremental learning for robust visual tracking[J]. International Journal of Computer Vision, 77, 125-141(2008). http://link.springer.com/article/10.1007%2Fs11263-007-0075-7

    [3] Zhao G P, Shen Y P, Wang J Y. Adaptive feature fusion object tracking based on circulant structure with kernel[J]. Acta Optica Sinica, 37, 0815001(2017).

    [4] Zhou H Y, Yang Y, Wang S Y. Multiple object tracking algorithm based on kernel correlation filter[J]. Laser & Optoelectronics Progress, 55, 091502(2018).

    [5] Mei X, Ling H B. Robust visual tracking using ℓ1 minimization. [C]∥2009 IEEE 12th International Conference on Computer Vision, September 29-October 2, 2009, Kyoto, Japan. New York: IEEE, 1436-1443(2009).

    [6] Liu B Y, Huang J Z, Yang L et al. Robust tracking using local sparse appearance model and K-selection. [C]∥CVPR 2011, June 20-25, 2011, Colorado Springs, CO, USA. New York: IEEE, 1313-1320(2011).

    [7] Zhong W, Lu H C, Yang M H. Robust object tracking via sparsity-based collaborative model. [C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition, June 16-21, 2012, Providence, RI, USA. New York: IEEE, 1838-1845(2012).

    [8] Zhuang B H, Lu H C, Xiao Z Y et al. Visual tracking via discriminative sparse similarity map[J]. IEEE Transactions on Image Processing, 23, 1872-1881(2014).

    [9] Wang D, Lu H C, Yang M H. Robust visual tracking via least soft-threshold squares[J]. IEEE Transactions on Circuits and Systems for Video Technology, 26, 1709-1721(2016). http://ieeexplore.ieee.org/document/7172503/

    [10] Wu Z P, Yang J, Liu H B et al. A real-time object tracking via L2-RLS and compressed Haar-like features matching[J]. Multimedia Tools and Applications, 75, 9427-9443(2016).

    [11] Kalal Z, Matas J, Mikolajczyk K. P-N learning: bootstrapping binary classifiers by structural constraints. [C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 49-56(2010).

    [12] Prasanna D, Prabhakar M. An effiecient human tracking system using Haar-like and hog feature extraction[J]. Cluster Computing, 22, 2993-3000(2019).

    [13] Zhang K H, Zhang L, Yang M H. Fast compressive tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 2002-2015(2014).

    [14] Wu Y, Lim J, Yang M H. Online object tracking: a benchmark. [C]∥2013 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2013, Portland, OR, USA. New York: IEEE, 2411-2418(2013).

    [15] Xiao Z Y, Lu H C, Wang D. Object tracking with L2-RLS. [C]∥Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), November 11-15, 2012, Tsukuba, Japan. New York: IEEE, 1351-1354(2012).

    [16] Jia X, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model. [C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition, June 16-21, 2012, Providence, RI, USA. New York: IEEE, 1822-1829(2012).

    [17] Henriques J F, Caseiro R, Martins P et al. High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 583-596(2015).

    Kaichuan Sun, Chenhua Liu, Guangshun Yao, Dawei Yang. Visual Tracking Combined Least Soft-Threshold Squares with Haar-like Feature Matching[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241001
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