• Laser & Optoelectronics Progress
  • Vol. 57, Issue 22, 221507 (2020)
Jing Zhang, Zhihui Hao, and Jing Liu*
Author Affiliations
  • School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
  • show less
    DOI: 10.3788/LOP57.221507 Cite this Article Set citation alerts
    Jing Zhang, Zhihui Hao, Jing Liu. Template-Updating Algorithm Based on Optical Flow Mapping in Object Tracking[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221507 Copy Citation Text show less
    References

    [1] Chen Y F, Wu Y, Zhang W. Survey of target tracking algorithm based on siamese network structure[J]. Computer Engineering and Applications, 56, 10-18(2020).

    [2] Yilmaz A, Javed O, Shah M. Object tracking: a survey[J]. ACM Computing Surveys, 38, 13-58(2006).

    [3] Danelljan M, Robinson A, Shahbaz Khan F et al. Beyond correlation filters: learning continuous convolution operators for visual tracking[M]. //Leibe B, Matas J, Sebe N, et al. Computer vision—ECCV 2016. Lecture notes in computer science. Cham: Springer, 9909, 472-488(2016).

    [4] Danelljan M, Bhat G, Khan F S et al. ECO: efficient convolution operators for tracking. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6931-6939(2017).

    [5] Meng L, Li C X[J]. Kernel correlation filtering algorithm based on a dual-feature model Journal of Image and Graphics, 2019, 2183-2199.

    [6] Danelljan M, Häger G, Khan F S et al. Learning spatially regularized correlation filters for visual tracking. [C]//2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 4310-4318(2015).

    [7] Wang D W, Xu C X, Liu Y. Kernelized correlation filter for target tracking with multi-feature fusion[J]. Computer Engineering and Design, 40, 3463-3468(2019).

    [8] Danelljan M, Häger G, Khan F S et al. Adaptive decontamination of the training set: a unified formulation for discriminative visual tracking. [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1430-1438(2016).

    [9] Galoogahi H K, Fagg A, Lucey S. Learning background-aware correlation filters for visual tracking. [C]//2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 1144-1152(2017).

    [10] Wang K Y, Chen Z G, Fu Y. Target anti-occlusion algorithm based on correlation filter[J]. Laser & Optoelectronics Progress, 56, 030401(2019).

    [11] Yang Y G, Shang Z H. Object Tracking Algorithm Based on Correlation Filtering and Convolution Residuals Learning[J]. Laser & Optoelectronics Progress, 57, 121012(2020).

    [12] Cheng Y, Li J Z, Zhu L N et al. Correlation filter tracking algorithm based on model and scale updating[J]. Laser & Optoelectronics Progress, 55, 121015(2018).

    [13] Yu Y Y, Shi Z L, Liu Y P. Foreground-aware based spatiotemporal correlation filter tracking algorithm[J]. Laser & Optoelectronics Progress, 56, 221503(2019).

    [14] Li J P, Shang Z H, Liu H. Visual object tracking algorithm based on correlation filters with hierarchical convolutional features[J]. Computer Science, 46, 252-257(2019).

    [15] Wang M M, Liu Y, Huang Z Y. Large margin object tracking with circulant feature maps. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 4800-4808(2017).

    [16] Danelljan M, Bhat G, Khan F S et al. ATOM: accurate tracking by overlap maximization. [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 4655-4664(2019).

    [17] Bertinetto L, Valmadre J, Henriques J F et al. Fully-convolutional siamese networks for object tracking[M]. //Hua G, Jégou H. Computer vision-ECCV 2016 workshops. Lecture notes in computer science. Cham: Springer, 9914, 850-865(2016).

    [18] Ren J M, Gong N S, Han Z Y. Improved target tracking algorithm based on siamese convolution neural network[J]. Journal of Chinese Computer Systems, 40, 2686-2690(2019).

    [19] Li B, Wu W, Wang Q et al. SiamRPN++: evolution of Siamese visual tracking with very deep networks. [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 4277-4286(2019).

    [20] Zhou D Y, Duan X P[J]. Target tracking method based on siamese network and attention mechanism Information & Communications, 2019, 61-63.

    [21] Ilg E, Mayer N, Saikia T et al. FlowNet 2.0: evolution of optical flow estimation with deep networks. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 1647-1655(2017).

    [22] Yang T, Chan A B. Learning dynamic memory networks for object tracking[M]. //Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision—ECCV 2018. Lecture notes in computer science. Cham: Springer, 11213, 153-169(2018).

    [23] Paszke A, Gross S, Massa F, high-performance deep learning library[EB/OL] et al. -12-03)[2020-03-05], org/abs/1912, 01703(2019). https://arxiv.

    [24] Bertinetto L, Valmadre J, Golodetz S et al. Staple: complementary learners for real-time tracking. [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1401-1409(2016).

    [25] Zhang Z P, Peng H W. Deeper and wider Siamese networks for real-time visual tracking. [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 4586-4595(2019).

    [26] Li X, Ma C, Wu B Y et al. Target-aware deep tracking. [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 1369-1378(2019).

    [27] Fan H, Ling H B. Siamese cascaded region proposal networks for real-time visual tracking. [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 7944-7953(2019).

    [28] Wang G T, Luo C, Xiong Z W et al. SPM-tracker: series-parallel matching for real-time visual object tracking. [C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 3638-3647(2019).

    Jing Zhang, Zhihui Hao, Jing Liu. Template-Updating Algorithm Based on Optical Flow Mapping in Object Tracking[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221507
    Download Citation