• Infrared and Laser Engineering
  • Vol. 47, Issue 12, 1226004 (2018)
Ge Baoyi*, Zuo Xianzhang, Hu Yongjiang, and Zhang Yan
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3788/irla201847.1226004 Cite this Article
    Ge Baoyi, Zuo Xianzhang, Hu Yongjiang, Zhang Yan. Object tracking algorithm based on two-step correlation filter[J]. Infrared and Laser Engineering, 2018, 47(12): 1226004 Copy Citation Text show less
    References

    [1] Bolme D S, Beveridge J R, Draper B A, et al. Visual object tracking using adaptive correlation filters [C]//Computer Vision and Pattern Recognition(CVPR), 2010: 2544-2550.

    [2] 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, 2015, 37(3): 583-596.

    [3] Li Y, Zhu J. A scale adaptive kernel correlation filter tracker with feature integration[C]//European Conference on Computer Vision, 2014: 254-265.

    [5] Ma C, Huang J B, Yang X, et al. Hierarchical convolutional features for visual tracking[C]//Proceedings of the IEEE International Conference on Computer Vision, 2015: 3074-3082.

    [6] Liu T, Wang G, Yang Q. Real-time part-based visual tracking via adaptive correlation filters[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015: 4902-4912.

    [7] Zhang Difei, Zhang Jinsuo, Yao Keming, et al. Infrared ship-target recognition based on SVM classification[J]. Infrared and Laser Engineering, 2016, 45(1): 0104004. (in Chinese)

    [8] Luo Haibo, Xu Lingyun, Hui Bin, et al. Status and prospect of target tracking based on deep learning[J]. Infrared and Laser Engineering, 2017, 46(5): 0502002. (in Chinese)

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

    [10] Jiang Shan, Zhang Rui, Han Guangliang, et al. Moving object tracking based on multi-feature fusion in the complex background gray image[J]. Chinese Optics, 2016, 9(3): 320-328. (in Chinese)

    [11] Wang Wei, Wang Chunping, Li Jun, et al. Correlation filter tracking based on feature fusing and model adaptive updating[J]. Optics and Precision Engineering, 2016, 24(8): 2059-2066. (in Chinese)

    [12] Yang Dedong, Cai Yuzhu, Mao Ning, et al. Long-term object tracking based on kernelized correlation filters[J]. Optics and Precision Engineering, 2016, 24(8): 2037-2049. (in Chinese)

    [13] Wang M, Liu Y, Huang Z. Large margin object tracking with circulant feature maps[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017: 21-26.

    [14] Wu Y, Lim J, Yang M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 37(9): 1834-1848.

    [15] Babenko B, Yang M H, Belongie S. Visual tracking with online multiple instance learning[C]//Computer Vision and Pattern Recognition, 2009: 983-990.

    [16] Kalal Z, Matas J, Mikolajczyk K. P-N learning: Bootstrapping binary classifiers by structural constraints [C]//Computer Vision and Pattern Recognition, 2010: 49-56.

    [17] Hare S, Saffari A, Torr P H S. Struck: Structured output tracking with kernels[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2016, 38(10): 2096-2109.

    [18] Zhang Lei, Wang Yanjie, Sun Honghai, et al. Adaptive scale object tracking with kernelized correlation filters[J]. Optics and Precision Engineering, 2016, 24(2): 448-459. (in Chinese)

    Ge Baoyi, Zuo Xianzhang, Hu Yongjiang, Zhang Yan. Object tracking algorithm based on two-step correlation filter[J]. Infrared and Laser Engineering, 2018, 47(12): 1226004
    Download Citation