[1] 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. [2] 熊昌镇,车满强,王润玲.基于稀疏卷积特征和相关滤波的实时视觉跟踪算法[J].计算机应用,2018,38(8):2175-2179,2223.(XIONG C Z, CHE M Q, WANG R L. Real-time visual tracking algorithm based on correlation filters and sparse convolutional features[J]. Journal of Computer Applications, 2018, 38(8):2175-2179, 2223.) [3] 樊佳庆,宋慧慧,张开华.通道稳定性加权补充学习的实时视觉跟踪算法[J].计算机应用,2018,38(6):1751-1754.(FAN J Q, SONG H H, ZHANG K H. Real-time visual tracking algorithm via channel stability weighted complementary learning[J]. Journal of Computer Applications, 2018, 38(6):1751-1754.) [4] 朱明敏,胡茂海.基于相关滤波器的长时视觉目标跟踪方法[J].计算机应用,2017,37(5):1466-1470.(ZHU M M, HU M H. Long-term visual object tracking algorithm based on correlation filter[J]. Journal of Computer Applications, 2017, 37(5):1466-1470.) [5] BERTINETTO L, VALMADRE J, HENRIQUES J F, et al. Fully-convolutional Siamese networks for object tracking[C]//ECCV 2016:Proceedings of the 2016 European Conference on Computer Vision, LNCS 9914. Cham:Springer, 2016:850-865. [6] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks[C]//NIPS 2012:Proceedings of the 25th International Conference on Neural Information Processing Systems. North Miami Beach, FL:Curran Associates Inc., 2012:1097-1105. [7] TAO R, GAVVES E, SMEULDERS A W M. Siamese instance search for tracking[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2016:1420-1429. [8] HUANG C, LUCEY S, RAMANAN D. Learning policies for adaptive tracking with deep feature cascades[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision. Piscataway, NJ:IEEE, 2017:105-114. [9] VALMADRE J, BERTINETTO L, HENRIQUES J, et al. End-to-end representation learning for correlation filter based tracking[C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2017:5000-5008. [10] GUO Q, FENG W, ZHOU C, et al. Learning dynamic Siamese network for visual object tracking[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision. Piscataway, NJ:IEEE, 2017:1781-1789. [11] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2016:770-778. [12] SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition[EB/OL].[2019-10-16]. http://www.cs.cmu.edu/~jeanoh/16-785/papers/simonyan-iclr2015-vgg.pdf. [13] RUSSAKOVSKY O, DENG J, SU H, et al. ImageNet large scale visual recognition challenge[J]. International Journal of Computer Vision, 2015, 115(3):211-252. [14] ABADI M, BARHAM P, CHEN J M, et al. TensorFlow:a system for large-scale machine learning[C]//OSDI 2016:Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation. Berkeley, CA:USENIX Association, 2016:265-283. [15] WU Y, LIM J, YANG M H. Online object tracking:a benchmark[C]//CVPR 2013:Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC:IEEE Computer Society, 2013:2411-2418. [16] WU Y, LIM J, YANG M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(9):1834-1848. [17] KRISTAN M, LEONARDIS A, MATAS J, et al. The visual object tracking VOT2017 challenge results[C]//ICCVW 2017:Proceedings of the 2017 IEEE International Conference on Computer Vision Workshop. Piscataway, NJ:IEEE, 2017:1949-1972. [18] DANELLJAN M, HÄGER G, KHAN F, et al. Accurate scale estimation for robust visual tracking[C]//Proceedings of the 2014 British Machine Vision Conference. Durham, UK:BMVA Press, 2014:65.1-65.11. [19] DANELLJAN M, HAGER G, KHAN F S, et al. Learning spatially regularized correlation filters for visual tracking[C]//ICCV 2015:Proceedings of the 2015 IEEE International Conference on Computer Vision. Piscataway, NJ:IEEE, 2015:4310-4318. |