[1] Bolme D S, Beveridge J R, Draper B A et al. Visual object tracking using adaptive correlation filters. [C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 2544-2550(2010).

[2] Henriques J F, Caseiro R, Martins P et al. Exploiting the circulant structure of tracking-by-detection with kernels[M]. ∥Fitzgibbon A, Lazebnik S, Perona P, et al. Lecture notes in computer science. Berlin, Heidelberg: Springer, 7575, 702-715(2012).

[3] Danelljan M, Khan F S, Felsberg M et al. Adaptive color attributes for real-time visual tracking. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 1090-1097(2014).

[4] 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://doi.ieeecomputersociety.org/10.1109/TPAMI.2014.2345390

[5] Danelljan M, Häger G, Khan F S 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, 4310-4318(2015).

[6] Wang X, Hou Z Q, Yu W S et al. Target scale adaptive robust tracking based on fusion of multilayer convolutional features[J]. Acta Optica Sinica, 37, 1115005(2017).

[7] Cai Y Z, Yang D D, Mao N et al. Visual tracking algorithm based on adaptive convolutional features[J]. Acta Optica Sinica, 37, 0315002(2017).

[8] Li C, Lu C Y, Zhao X et al. Scale adaptive correlation filtering tracing algorithm based on feature fusion[J]. Acta Optica Sinica, 38, 0515001(2018).

[9] Wang H Y, Wang L, Yin W R et al. Multi-scale correlation filtering visual tracking algorithm combined with target detection[J]. Acta Optica Sinica, 39, 0115004(2019).

[10] Wang N Y, Yeung D Y. Learning a deep compact image representation for visual tracking. [C]∥Proceedings of the 26th International Conference on Neural Information Processing Systems, December 5-10, 2013, Lake Tahoe, Nevada. USA: Curran Associates Inc., 1, 809-817(2013).

[11] Wang N, Li S, Gupta A et al. -04-23)[2019-01-06]. https:∥arxiv., org/abs/1501, 04587(2015).

[12] Ma C, Huang J B, Yang X K et al. Hierarchical convolutional features for visual tracking. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 3074-3082(2015).

[13] Ma C, Huang J B, Yang X K, Machine Intelligence, Early Accesset al. Robust visual tracking via hierarchical convolutional features[J]. -08-13) [2019-01-06](2018).

[14] Wang L J, Ouyang W L, Wang X G et al. Visual tracking with fully convolutional networks. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 3119-3127(2015).

[15] 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).

[16] Bertinetto L, Valmadre J, Henriques J F et al. Fully-convolutional Siamese networks for object tracking[M]. ∥Hua G, Jégou H. Lecture notes in computer science. Cham: Springer, 9914, 850-865(2016).

[17] Valmadre J, Bertinetto L, Henriques J et al. End-to-end representation learning for correlation filter based tracking. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 5000-5008(2017).

[18] Tao R, Gavves E. Smeulders A W M. Siamese instance search for tracking. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1420-1429(2016).

[19] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).

[20] Simonyan K. -04-10)[2019-01-06]. https:∥arxiv., org/abs/1409, 1556(2015).

[21] Deng J, Dong W, Socher R et al. ImageNet: a large-scale hierarchical image database. [C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 20-25, 2009, Miami, FL, USA. New York: IEEE, 248-255(2009).

[22] Liu W, Anguelov D, Erhan D et al. SSD: single shot multibox detector. [C]∥Leibe B, Matas J, Sebe N, et al. Lecture notes in computer science. Cham: Springer, 9905, 21-37(2016).

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

[24] Mueller M, Smith N, Ghanem B. A benchmark and simulator for UAV tracking[M]. ∥Leibe B, Matas J, Sebe N, et al. Lecture notes in computer science. Cham: Springer, 9905, 445-461(2016).

[25] Wu Y, Lim J, Yang M H. Online object tracking: a benchmark. [C]∥2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 23-28, 2013, Portland, OR, USA. New York: IEEE, 2411-2418(2013).

[26] Jia X, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model. [C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 16-21, 2012, Providence, RI, USA. New York: IEEE, 1822-1829(2012).

[27] Hong S, You T, Kwak S et al. Online tracking by learning discriminative saliency map with convolutional neural network. [C]∥Proceedings of the 32nd international Conference on Machine Learning, July 6-11, 2015, Lille, France. Massachusetts: JMLR. org, 37, 597-606(2015).

[28] Danelljan M, Häger G, Khan F S et al. Accurate scale estimation for robust visual tracking[C]∥Proceedings of the British Machine Vision Conference 2014, September 1-5, 2014, Nottingham. Durham, England,, 1-11(2014).

[29] Ma C, Huang J B, Yang X K et al. Adaptive correlation filters with long-term and short-term memory for object tracking[J]. International Journal of Computer Vision, 126, 771-796(2018). http://link.springer.com/10.1007/s11263-018-1076-4