• Laser & Optoelectronics Progress
  • Vol. 56, Issue 12, 121501 (2019)
Huan Liu, Chungeng Li*, Jubai An, Guo Wei, and Junli Ren
Author Affiliations
  • Information Science and Technology College, Dalian Maritime University, Dalian, Liaoning 116026, China
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    DOI: 10.3788/LOP56.121501 Cite this Article Set citation alerts
    Huan Liu, Chungeng Li, Jubai An, Guo Wei, Junli Ren. Multiple Object Tracking Based on Kernelized Correlation Filter[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121501 Copy Citation Text show less
    References

    [1] Leal-Taixé L, Milan A, Reid I et al. towards a benchmark for multi-target tracking[EB/OL][2018-11-25]. 2018-04-08) https:∥arxiv., org/abs/1504, 01942(2015).

    [2] Kim C, Li F X, Ciptadi A et al. Multiple hypothesis tracking revisited. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 4696-4704(2015).

    [3] Xiang Y, Alahi A, Savarese S. Learning to track: online multi-object tracking by decision making. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 4705-4713(2015).

    [4] Chen L, Ai H Z, Shang C et al. Online multi-object tracking with convolutional neural networks. [C]∥2017 IEEE International Conference on Image Processing (ICIP), September 17-20, 2017, Beijing, China. New York: IEEE, 645-649(2017).

    [5] Milan A, Roth S, Schindler K. Continuous energy minimization for multitarget tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 58-72(2014). http://www.ncbi.nlm.nih.gov/pubmed/24231866

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

    [7] Bochinski E, Eiselein V, Sikora T. High-speed tracking-by-detection without using image information. [C]∥2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), August 29-September 1, 2017, Lecce, Italy. New York: IEEE, 8078516(2017).

    [8] Bewley A, Ge Z Y, Ott L et al. Simple online and realtime tracking. [C]∥2016 IEEE International Conference on Image Processing (ICIP), September 25-28, 2016, Phoenix, AZ, USA. New York: IEEE, 3464-3468(2016).

    [9] Wojke N, Bewley A, Paulus D. Simple online and realtime tracking with a deep association metric. [C]∥2017 IEEE International Conference on Image Processing (ICIP), September 17-20, 2017, Beijing, China. New York: IEEE, 3645-3649(2017).

    [10] 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). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6870486

    [11] Dalal N, Triggs B. Histograms of oriented gradients for human detection. [C]∥2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), June 20-25, 2005, San Diego, CA, USA. New York: IEEE, 886-893(2005).

    [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] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017). http://www.ncbi.nlm.nih.gov/pubmed/27295650

    [14] Tian Q, Yuan T Y, Yang D et al. A pedestrian detection method based on dark channel defogging and deep learning[J]. Laser & Optoelectronics Progress, 55, 111007(2018).

    [15] Kalman R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering, 82, 35-45(1960). http://gji.oxfordjournals.org/external-ref?access_num=10.1115/1.3662552&link_type=DOI

    [16] Pirsiavash H, Ramanan D, Fowlkes C C. Globally-optimal greedy algorithms for tracking a variable number of objects. [C]∥CVPR 2011, June 20-25, 2011, Colorado Springs, CO, USA. New York: IEEE, 1201-1208(2011).

    [17] Solera F, Calderara S, Cucchiara R. Learning to divide and conquer for online multi-target tracking. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 4373-4381(2015).

    [18] Bae S H, Yoon K J. Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 1218-1225(2014).

    [19] Sheng H, Zhang X Y, Zhang Y et al. Enhanced association with supervoxels in multiple hypothesis tracking[J]. IEEE Access, 7, 2107-2117(2019).

    [20] Dicle C, Camps O I, Sznaier M. The way they move: tracking multiple targets with similar appearance. [C]∥2013 IEEE International Conference on Computer Vision, December 1-8, 2013, Sydney, NSW, Australia. New York: IEEE, 2304-2311(2013).

    Huan Liu, Chungeng Li, Jubai An, Guo Wei, Junli Ren. Multiple Object Tracking Based on Kernelized Correlation Filter[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121501
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