[1] Wu X J, Xu T Y, Xu W B. Review of target tracking algorithms in video based on correlation filter[J]. Command Information System and Technology, 8, 1-5(2017).

[2] Baker S, Matthews I. Lucas-kanade 20 years on: A unifying framework[J]. International Journal of Computer Vision, 56, 221-255(2004). http://dl.acm.org/citation.cfm?id=964604

[3] Nguyen H T. Smeulders A W M. Fast occluded object tracking by a robust appearance filter[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26, 1099-1104(2004).

[4] Comaniciu D, Ramesh V, Meer P. Real-time tracking of non-rigid objects using mean shift. [C]∥Proceedings IEEE Conference on Computer Vision and Pattern Recognition, 142-149(2000).

[5] Babenko B, Yang M H, Belongie S. Visual tracking with online Multiple Instance Learning. [C]∥Computer Vision and Pattern Recognition, 983-990(2009).

[6] Kalal Z, Matas J, Mikolajczyk K. P-N learning: Bootstrapping binary classifiers by structural constraints. [C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 49-56(2010).

[7] Hare S, Saffari A. Torr P H S. Struck: Structured output tracking with kernels. [C]∥International Conference on Computer Vision, 263-270(2011).

[8] Mei X, Ling H. Robust visual tracking using L1 minimization[J]. IEEE International Conference on computer Vision. Kyoto: IEEE, 1436-1443(2009). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5459292

[9] Bolme D S, Beveridge J R, Draper B A et al. Visual object tracking using adaptive correlation filters. [C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2544-2550(2010).

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

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

[12] Danelljan M, Häger G, Shahbaz Khan F et al. Accurate scale estimation for robust visual tracking. [C]∥Proceedings of the British Machine Vision Conference 2014, British Machine Vision Conference(2014).

[13] Li Y, Zhu J K[M]. A scale adaptive kernel correlation filter tracker with feature integration, 254-265(2015).

[14] Bertinetto L, Valmadre J, Golodetz S et al. Staple: complementary learners for real-time tracking. [C]∥IEEE Computer Vision and Pattern Recognition, 1401-1409(2016).

[15] Yan H, Zhang Y, Yang X L et al. A kernelized correlation filters with occlusion handling[J]. Journal of Optoelectronics·Laser, 29, 647-652(2018).

[16] Bao X A, Zhan X J, Wang Q et al. Anti occlusion target tracking algorithm based on KCF and SIFT features[J]. Computer Measurement & Control, 26, 148-152(2018).

[17] Lü G J, Mao X, Hu Y J et al. A method of detecting and tracking occlusion based on comparison of forward and backward errors[J]. Infrared technology, 38, 337-341, 347(2016).

[18] Kalal Z, Mikolajczyk K, Matas J. Forward-backward error: automatic detection of tracking failures. [C]∥20 ^th International Conference on Pattern Recognition , 23-26(2010).

[19] Wan L, Bai H L, Dai J. Extended optimal Otsu thresholding method of image segmention[J]. Journal of Harbin Engineering University, 24, 326-329(2003).