激光与光电子学进展, 2020, 57 (22): 221507, 网络出版: 2020-11-12   

目标跟踪中基于光流映射的模板更新算法 下载: 890次

Template-Updating Algorithm Based on Optical Flow Mapping in Object Tracking
作者单位
天津大学电气自动化与信息工程学院, 天津 300072
引用该论文

张静, 郝志晖, 刘婧. 目标跟踪中基于光流映射的模板更新算法[J]. 激光与光电子学进展, 2020, 57(22): 221507.

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.

参考文献

[1] 陈云芳, 吴懿, 张伟. 基于孪生网络结构的目标跟踪算法综述[J]. 计算机工程与应用, 2020, 56(6): 10-18.

    Chen Y F, Wu Y, Zhang W. Survey of target tracking algorithm based on siamese network structure[J]. Computer Engineering and Applications, 2020, 56(6): 10-18.

[2] Yilmaz A, Javed O, Shah M. Object tracking: a survey[J]. ACM Computing Surveys, 2006, 38(4): 13-58.

[3] DanelljanM, RobinsonA, Shahbaz KhanF, 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, 2016, 9909: 472- 488.

[4] DanelljanM, BhatG, Khan FS, 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, 2017: 6931- 6939.

[5] 孟琭, 李诚新. 双特征模型核相关滤波目标跟踪算法[J]. 中国图象图形学报, 2019( 12): 2183- 2199.

    MengL, Li CX. Kernel correlation filtering algorithm based on a dual-feature model[J]. Journal of Image and Graphics, 2019( 12): 2183- 2199.

[6] DanelljanM, HägerG, Khan FS, 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, 2015: 4310- 4318.

[7] 王殿伟, 许春香, 刘颖. 基于多特征融合的核相关滤波目标跟踪算法[J]. 计算机工程与设计, 2019, 40(12): 3463-3468.

    Wang D W, Xu C X, Liu Y. Kernelized correlation filter for target tracking with multi-feature fusion[J]. Computer Engineering and Design, 2019, 40(12): 3463-3468.

[8] DanelljanM, HägerG, Khan FS, 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, 2016: 1430- 1438.

[9] Galoogahi HK, FaggA, LuceyS. 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, 2017: 1144- 1152.

[10] 王凯宇, 陈志国, 傅毅. 基于相关滤波器的目标抗遮挡算法[J]. 激光与光电子学进展, 2019, 56(3): 030401.

    Wang K Y, Chen Z G, Fu Y. Target anti-occlusion algorithm based on correlation filter[J]. Laser & Optoelectronics Progress, 2019, 56(3): 030401.

[11] 杨亚光, 尚振宏. 相关滤波融合卷积残差学习的目标跟踪算法[J]. 激光与光电子学进展, 2020, 57(12): 121012.

    Yang Y G, Shang Z H. Object Tracking Algorithm Based on Correlation Filtering and Convolution Residuals Learning[J]. Laser & Optoelectronics Progress, 2020, 57(12): 121012.

[12] 成悦, 李建增, 褚丽娜, 等. 基于模型与尺度更新的相关滤波跟踪算法[J]. 激光与光电子学进展, 2018, 55(12): 121015.

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

[13] 虞跃洋, 史泽林, 刘云鹏. 基于前景感知的时空相关滤波跟踪算法[J]. 激光与光电子学进展, 2019, 56(22): 221503.

    Yu Y Y, Shi Z L, Liu Y P. Foreground-aware based spatiotemporal correlation filter tracking algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(22): 221503.

[14] 李健鹏, 尚振宏, 刘辉. 融合多层卷积特征的相关滤波运动目标跟踪算法[J]. 计算机科学, 2019, 46(7): 252-257.

    Li J P, Shang Z H, Liu H. Visual object tracking algorithm based on correlation filters with hierarchical convolutional features[J]. Computer Science, 2019, 46(7): 252-257.

[15] Wang MM, LiuY, Huang ZY. 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, 2017: 4800- 4808.

[16] DanelljanM, BhatG, Khan FS, 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, 2019: 4655- 4664.

[17] BertinettoL, ValmadreJ, Henriques JF, 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, 2016, 9914: 850- 865.

[18] 任珈民, 宫宁生, 韩镇阳. 一种改进的基于孪生卷积神经网络的目标跟踪算法[J]. 小型微型计算机系统, 2019, 40(12): 2686-2690.

    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, 2019, 40(12): 2686-2690.

[19] LiB, WuW, WangQ, 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, 2019: 4277- 4286.

[20] 周迪雅, 段喜萍. 基于孪生网络与注意力机制的目标跟踪方法[J]. 信息通信, 2019( 12): 61- 63.

    Zhou DY, Duan XP. Target tracking method based on siamese network and attention mechanism[J]. Information & Communications, 2019( 12): 61- 63.

[21] IlgE, MayerN, SaikiaT, 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, 2017: 1647- 1655.

[22] YangT, Chan AB. 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, 2018, 11213: 153- 169.

[23] PaszkeA, GrossS, MassaF, et al., high-performance deep learninglibrary[EB/OL]. ( 2019-12-03)[2020-03-05]. org/abs/1912. 01703. https://arxiv.

[24] BertinettoL, ValmadreJ, GolodetzS, 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, 2016: 1401- 1409.

[25] Zhang ZP, Peng HW. 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, 2019: 4586- 4595.

[26] LiX, MaC, Wu BY, 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, 2019: 1369- 1378.

[27] FanH, Ling HB. 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, 2019: 7944- 7953.

[28] Wang GT, LuoC, Xiong ZW, 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, 2019: 3638- 3647.

张静, 郝志晖, 刘婧. 目标跟踪中基于光流映射的模板更新算法[J]. 激光与光电子学进展, 2020, 57(22): 221507. 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.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!