• Opto-Electronic Engineering
  • Vol. 47, Issue 1, 190279 (2020)
Tang Xuemeng1、*, Chen Zhiguo1, and Fu Yi1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.12086/oee.2020.190279 Cite this Article
    Tang Xuemeng, Chen Zhiguo, Fu Yi. Anti-occlusion and re-tracking of real-time moving target based on kernelized correlation filter[J]. Opto-Electronic Engineering, 2020, 47(1): 190279 Copy Citation Text show less
    References

    [2] Henriques J F, Caseiro R, Martins P, et al. Exploiting the circu-lant structure of tracking-by-detection with kernels[C]// Pro-ceedings of the 12th European Conference on Computer Vision, 2012: 702–715.

    [3] Comaniciu D, Meer P. Mean shift: a robust approach toward feature space analysis[J]. IEEE Transactions on Pattern Analy-sis and Machine Intelligence, 2002, 24(5): 603–619.

    [4] Mei X, Ling H B. Robust visual tracking and vehicle classification via sparse representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(11): 2259–2272.

    [5] Danelljan M, H.ger G, Khan F S, et al. Accurate scale estimation for robust visual tracking[C]//Proceedings of the British Machine Vision Conference, 2014.

    [6] Grabner H, Grabner M, Bischof H. Real-time tracking via on-line boosting[C]//Proceedings of the British Machine Vision Confe-rence, 2006, 1: 47–56.

    [8] Henriques J F, Caseiro R, Martins P, et al. High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pat-tern Analysis and Machine Intelligence, 2015, 37(3): 583–596.

    [9] Danelljan M, Khan F S, Felsberg M, et al. Adaptive color attributes for real-time visual tracking[C]//Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014: 1090–1097.

    [10] Danelljan M, H.ger G, Khan F S, et al. Learning spatially regu-larized correlation filters for visual tracking[C]//Proceedings of 2015 IEEE International Conference on Computer Vision, 2015: 4310–4318.

    [11] Bertinetto L, Valmadre J, Golodetz S, et al. Staple: complemen-tary learners for real-time tracking[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016: 1401–1409.

    [12] Valmadre J, Bertinetto L, Henriques J, et al. End-to-end repre-sentation learning for correlation filter based track-ing[C]//Proceedings of 2017 IEEE Conference on Computer Vi-sion and Pattern Recognition, 2017: 5000–5008.

    [13] Danelljan M, Bhat G, Khan F S, et al. Eco: efficient convolution operators for tracking[C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017: 6931–6939.

    [16] Li F, Tian C, Zuo W M, et al. Learning spatial-temporal regula-rized correlation filters for visual tracking[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018: 4904–4913.

    [17] Li Y, ZhuJ K, Hoi S C H, et al. Robust estimation of similarity transformation for visual object tracking[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2019, 33: 8666–8673.

    [18] Xu TY, Feng Z H, Wu X J, et al. Learning adaptive discriminative correlation filters via temporal consistency preserving spatial feature selection for robust visual tracking[C]//Proceedings of 2019 IEEE Conference on Computer Vision and Pattern Rec-ognition (CVPR), 2019.

    [19] Li B, Yan J J, Wu W, et al. High performance visual tracking with Siamese region proposal network[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recog-nition, 2018: 8971–8980.

    [20] Li B, Wu W, Wang Q, et al. SiamRPN++: evolution of Siamese visual tracking with very deep networks[C]//Proceedings of 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

    [22] Fan H, Lin L T, Yang F, et al. LaSOT: a high-quality benchmark for large-scale single object tracking[C]//Proceedings of 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

    [23] Faragher R. Understanding the basis of the Kalman filter via a simple and intuitive derivation [lecture notes][J]. IEEE Signal Processing Magazine, 2012, 29(5): 128–132.

    [24] Bolme D S, Beveridge J R, Draper B A, et al. Visual object tracking using adaptive correlation filters[C]//Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010: 2544–2550.

    [25] Li Y, Zhu J K. A scale adaptive kernel correlation filter tracker with feature integration[C]//Computer Vision-ECCV 2014 Work-shops, 2014: 254–265.

    Tang Xuemeng, Chen Zhiguo, Fu Yi. Anti-occlusion and re-tracking of real-time moving target based on kernelized correlation filter[J]. Opto-Electronic Engineering, 2020, 47(1): 190279
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