• Laser & Optoelectronics Progress
  • Vol. 57, Issue 24, 241008 (2020)
Dianwei Wang1、*, Haoyu Fang1、*, Ying Liu1, Jing Jiang1, Xincheng Ren2, Zhijie Xu3, and Yongrui Qin3
Author Affiliations
  • 1School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121, China
  • 2School of Physics and Electronic Information, Yan'an University, Yan'an, Shaanxi 716000, China
  • 3School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH UK
  • show less
    DOI: 10.3788/LOP57.241008 Cite this Article Set citation alerts
    Dianwei Wang, Haoyu Fang, Ying Liu, Jing Jiang, Xincheng Ren, Zhijie Xu, Yongrui Qin. Algorithm for Panoramic Video Tracking Based on Improved SiameseRPN[J]. Laser & Optoelectronics Progress, 2020, 57(24): 241008 Copy Citation Text show less
    References

    [1] Lu H C, Li P X, Wang D. Visual object tracking: a survey[J]. Pattern Recognition and Artificial Intelligence, 31, 61-76(2018).

    [2] Cai Z W, Wen L Y, Lei Z et al. Robust deformable and occluded object tracking with dynamic graph[J]. IEEE Transactions on Image Processing, 23, 5497-5509(2014). http://www.ncbi.nlm.nih.gov/pubmed/25350927

    [3] Zhou Y, Zhou Z, Chen K et al. Persistent object tracking in road panoramic videos[M]. ∥Lin W, Wu D, Ho A, et al. Advances in multimedia information processing——PCM 2012. Lecture notes in computer science. Heidelberg: Springer, 7674, 359-368(2012).

    [4] Nam H, Han B. Learning multi-domain convolutional neural networks for visual tracking. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 4293-4302(2016).

    [5] Yun S, Choi J, Yoo Y et al. Action-decision networks for visual tracking with deep reinforcement learning. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 1349-1358(2017).

    [6] Jung I, Son J, Baek M et al. Real-time MDNet[M]. ∥ Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision——ECCV 2018. Lecture notes in computer science. Cham: Springer, 11208, 89-104(2018).

    [7] Howard A, Sandler M, Chu G et al. -11-20)[2020-01-18 ]. https:∥arxiv., org/abs/1905, 02244(2019).

    [8] Li B, Yan J J, Wu W et al. High performance visual tracking with Siamese region proposal network. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 18311819(2018).

    [9] 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).

    [10] 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).

    [11] Kristan M, Leonardis A, Matas J et al. The sixth visual object tracking VOT2018 challenge results[M]. ∥ Leal-Taixé L, Roth S. Computer vision——ECCV 2018 workshops. Lecture notes in computer science. Cham: Springer, 11129, 3-53(2019).

    [12] Yang D W, Gong X F, Mao L et al. Multi-domain convolutional neural network tracking algorithm based on reconstructed feature combination[J]. Laser & Optoelectronics Progress, 56, 191501(2019).

    [13] Li Y, Yang D D, Han Y J et al. Siamese neural network object tracking with distractor-aware model[J]. Acta Optica Sinica, 40, 0415002(2020).

    [14] Liu M J, Cao Y Z, Zhu S Y et al. Feature fusion video target tracking method based on convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 041502(2020).

    [15] Tan M X, Chen B, Pang R M et al. MnasNet: platform-aware neural architecture search for mobile. [C]∥2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 2815-2823(2019).

    [16] Yang T J, Howard A, Chen B et al. NetAdapt: platform-aware neural network adaptation for mobile applications[M]. ∥ Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision——ECCV 2018. Lecture notes in computer science. Cham: Springer, 11214, 289-304(2018).

    [17] Howard A G, Zhu M L, Chen B et al. -04-17)[2020-01-18 ]. https:∥arxiv., org/abs/1704, 04861(2017).

    [18] Hu J, Shen L, Sun G. Squeeze-and-excitation networks. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 7132-7141(2018).

    [19] 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).

    [20] Shen Y L, Wu Z D, Zhao R J et al. Long-term object tracking based on model updating and fast re-detection[J]. Acta Optica Sinica, 40, 0315002(2020).

    [21] 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).

    Dianwei Wang, Haoyu Fang, Ying Liu, Jing Jiang, Xincheng Ren, Zhijie Xu, Yongrui Qin. Algorithm for Panoramic Video Tracking Based on Improved SiameseRPN[J]. Laser & Optoelectronics Progress, 2020, 57(24): 241008
    Download Citation