[1] A. Yilmaz, O. Javed, and M. Shah, "Object tracking: A survey,'' ACM Comput. Surv., vol. 38, no. 4, pp. 1-45, 2006.

[2] H. Yang, L. Shao, F. Zheng, L. Wang, and Z. Song, "Recent advances and trends in visual tracking: A review,'' Neurocomputing, vol. 74, no. 18, pp. 3823-3831, Nov. 2011.

[3] D. Wang, H. Lu, and M.-H. Yang, "Online object tracking with sparse prototypes,'' IEEE Trans. Image Process., vol. 22, no. 1, pp. 314-325, Jan. 2013.

[4] Y. Wu, J. Lim, and M.-H. Yang, "Online object tracking: A benchmark,'' in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 2411-2418.

[5] D. Comaniciu, V. Ramesh, and P. Meer, "Kernel-based object tracking,'' IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 5, pp. 564-577, May 2003.

[6] X. Mei and H. Ling, "Robust visual tracking using L1-minimization,'' in Proc. IEEE Int. Conf. Comput. Vis. (ICCV), Sep./Oct. 2009, pp. 1436-1443.

[7] C. Bao, Y. Wu, H. Ling, and H. Ji, "Real time robust L1-tracker using accelerated proximal gradient approach,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recogn. (CVPR), Jun. 2012, pp. 1830-1837.

[8] B. K. S.Kumar, M. N. S. Swamy, and M. O. Ahmad, "Structural local DCT sparse appearance model for visual tracking,'' in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), May 2015, pp. 1194-1197.

[9] X. Jia, H. Lu, and M.-H. Yang, "Visual tracking via adaptive structural local sparse appearance model,'' in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2012, pp. 1822-1829.

[10] A. Adam, E. Rivlin, and I. Shimshoni, "Robust fragments-based tracking using the integral histogram,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., New York, NY, USA, Jun. 2006, pp. 798-805.

[11] J. Yang, R. Xu, J. Cui, and Z. Ding, "Robust visual tracking using adaptive local appearance model for smart transportation,'' Multimedia Tools Appl., vol. 75, no. 24, pp. 17487-17500, Dec. 2016.

[12] B. K. S. Kumar, M. N. S. Swamy, and M. O. Ahmad, "Visual tracking using structural local DCT sparse appearance model with occlusion detection,'' Multimedia Tools and Applications. Cham, Switzerland: Springer, 2018, pp. 1-24.

[13] D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang, "Incremental learning for robust visual tracking,'' Int. J. Comput. Vis., vol. 77, no. 1-3, pp. 125-141, 2008.

[14] B. K. S. Kumar, M. N. S. Swamy, and M. O. Ahmad, "Weighted residual minimization in PCA subspace for visual tracking,'' in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), May 2016, pp. 986-989.

[15] H. Wang, H. Ge, and S. Zhang, "Object tracking via 2DPCA and L2-regularization,'' J. Elect. Comput. Eng., vol. 2016, Jul. 2016, Art. no. 7975951.

[16] D. Wang and H. Lu, "Object tracking via 2DPCA and L1-regularization,'' IEEE Signal Process. Lett., vol. 19, no. 11, pp. 711-714, Nov. 2012. 

[17] B. K. S. Kumar, M. N. S. Swamy, and M. O. Ahmad, "Visual tracking via bilateral 2DPCA and robust coding,'' in Proc. IEEE Can. Conf. Elect. Comput. Eng. (CCECE), May 2016, pp. 1-4.

[18] P. Qu, "Visual tracking with fragments-based PCA sparse representation,'' Int. J. Signal Process., Image Process. Pattern Recognit., vol. 7, no. 2, pp. 23-34, Feb. 2014.

[19] M. Sun, D. Du, H. Lu, and L. Zhang, "Visual tracking with a structured local model,'' in Proc. IEEE Int. Conf. Image Process. (ICIP), Sep. 2015, pp. 2855-2859.

[20] B. Babenko, M.-H. Yang, and S. Belongie, "Visual tracking with online multiple instance learning,'' in Proc. CVPR, Jun. 2009, pp. 983-990.

[21] H. Grabner, C. Leistner, and H. Bischof, "Semi-supervised on-line boosting for robust tracking,'' in Proc. Eur.Conf. Comput. Vis. (ECCV), Oct. 2008, pp. 234-247.

[22] F. Wang, J. Zhang, Q. Guo, P. Liu, and D. Tu, "Robust visual tracking via discriminative structural sparse feature,'' in Proc. Chin. Conf. Image Graph. Technol., Jun. 2015, pp. 438-446.

[23] W. Zhong, H. Lu, and M.-H. Yang, "Robust object tracking via sparse collaborative appearance model,'' IEEE Trans. Image Process., vol. 23, no. 5, pp. 2356-2368, May 2014.

[24] C. Xie, J. Tan, P. Chen, J. Zhang, and L. He, "Collaborative object tracking model with local sparse representation,'' J. Vis. Commun. Image Represent., vol. 25, no. 2, pp. 423-434, 2014.

[25] B. Zhuang, L. Wang, and H. Lu, "Visual tracking via shallow and deep collaborative model,'' Neurocomputing, vol. 218, pp. 61-71, Dec. 2016.

[26] H. Zhang, F. Tao, and G. Yang, "Robust visual tracking based on structured sparse representation model,'' Multimedia Tools Appl., vol. 74, no. 3, pp. 1021-1043, 2015.

[27] C. Ma, J. Huang, X. Yang, and M. Yang, "Hierarchical convolutional features for visual tracking,'' in Proc. IEEE Int. Conf. Comput. Vis. (ICCV), Jun. 2015, pp. 3074-3082.

[28] Y. Qi, S. Zhang, L. Qin, H. Yao, Q. Huang, J. Lim, and M.-H. Yang, "Hedged deep tracking,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2016, pp. 4303-4311.

[29] M. Danelljan, A. Robinson, F. S. Khan, and M. Felsberg, "Beyond correlation filters: Learning continuous convolution operators for visual tracking,'' in Proc. Eur. Conf. Comput. Vis. (ECCV), Oct. 2016, pp. 472-488.

[30] H. Nam and B. Han, "Learning multi-domain convolutional neural networks for visual tracking,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2016, pp. 4293-4302.

[31] D. Bolme, J. Beveridge, B. Draper, and Y. Lui, "Visual object tracking using adaptive correlation filters,'' in Proc. Int. Conf. Comput. Vis. Pattern Recognit., Sep. 2010, pp. 2544-2550.

[32] J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, "Exploiting the circulant structure of tracking-by-detection with kernels,'' in Proc. Eur. Conf. Comput. Vis. (ECCV), Oct. 2012, pp. 702-715.

[33] J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, "High-speed tracking with kernelized correlation filters,'' IEEE Trans. Pattern Anal. Mach. Intell., vol. 37, no. 3, pp. 583-596, Mar. 2015.

[34] M. Danelljan, F. S. Khan, M. Felsberg, and J. van de Weijer, "Adaptive color attributes for real-time visual tracking,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recogn. (CVPR), Jun. 2014, pp. 1090-1097.

[35] M. Danelljan, G. Häger, F. Khan, and M. Felsberg, "Accurate scale estimation for robust visual tracking,'' in Proc. Brit. Mach. Vis. Conf. (BMVC), Sep. 2014, pp. 1-11.

[36] T. Zhang, A. Bibi, and B. Ghanem, "In defense of sparse tracking: Circulant sparse tracker,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2016, pp. 3880-3888.

[37] T. Wang, I. Y. H. Gu, and P. Shi, "Object tracking using incremental 2D-PCA learning and ML estimation,'' in Proc. IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), Apr. 2007, pp. I-933-I-936.

[38] H. Kong, L. Wang, E. K. Teoh, X. Li, J.-G. Wang, and R. Venkateswarlu, "Generalized 2D principal component analysis for face image representation and recognition,'' Neural Netw., vol. 18, nos. 5-6, pp. 585-594, Jul. 2005.

[39] M.-X. Jiang, M. Li, and H.-Y. Wang, "Visual object tracking based on 2DPCA and ML,'' Math. Problems Eng., vol. 2013, May 2013, Art. no. 404978.

[40] M. Yang, L. Zhang, J. Yang, and D. Zhang, "Robust sparse coding for face recognition,'' in Proc. IEEE Conf. Comput. Vis. Pattern Recogn. (CVPR), Jun. 2011, pp. 625-632.

[41] J. Yan and M. Tong, "Weighted sparse coding residual minimization for visual tracking,'' in Proc. Vis. Commun. Image Process. (VCIP), Nov. 2011, pp. 1-4.

[42] M. Jiang, H. Wang, and B. Wang, "Robust visual tracking based on maximum likelihood estimation,'' Int. J. Digit. Content Technol. Appl., vol. 6, no. 22, pp. 467-474, Dec. 2012.

[43] S. A. Siena, "Improving the design and use of correlation filters in visual tracking,'' Ph.D. dissertation, Dept. Elect. Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA, 2017.

[44] M. Isard and A. Blake, "CONDENSATION: Conditional density propagation for visual tracking,'' Int. J. Comput. Vis., vol. 29, no. 1, pp. 5-28, Aug. 1998.

[45] M. J. Black and A. D. Jepson, "EigenTracking: Robust matching and tracking of articulated objects using a view-based representation,'' Int. J. Comput. Vis., vol. 26, no. 1, pp. 63-84, 1998.

[46] D. Wang, H. Lu, and M.-H. Yang, "Robust visual tracking via least softthreshold squares,'' IEEE Trans. Circuits Syst. Video Technol., vol. 26, no. 9, pp. 1709-1721, Sep. 2016.

[47] M. Kristan, A. Leonardis, J. Matas, M. Felsberg, and R. P�ugfelder, "The visual object tracking VOT2016 challenge results,'' in Proc. Eur. Conf. Comput. Vis. (ECCV), Oct. 2016, pp. 777-823.

[48] M. Mueller, N. Smith, and B. Ghanem, "A benchmark and simulator for UAV tracking,'' in Proc. Eur. Conf. Comput. Vis. (ECCV), Oct. 2016, pp. 445-461.

[49] Y. Sui, Y. Tang, L. Zhang, and G. Wang, "Visual tracking via subspace learning: A discriminative approach,'' Int. J. Comput. Vis., vol. 126, no. 5, pp. 515-536, 2018.

[50] D. Wang, H. Lu, and C. Bo, "Visual tracking via weighted local cosine similarity,'' IEEE Trans. Cybern., vol. 45, no. 9, pp. 1838-1850, Sep. 2015.

[51] D. Wang, H. Lu, Z. Xiao, and M.-H. Yang, "Inverse sparse tracker with a locally weighted distance metric,'' IEEE Trans. Image Process., vol. 24, no. 9, pp. 2646-2657, Sep. 2015.

[52] D.Wang, H. Lu, and C. Bo, "Fast and robust object tracking via probability continuous outlier model,'' IEEE Trans. Image Process., vol. 24, no. 12, pp. 5166-5176, Dec. 2015.

[53] N. Wang and D.-Y. Yeung, "Learning a deep compact image representation for visual tracking,'' in Proc. Adv. Neural Inf. Process. Syst., 2013, pp. 809-817.

[54] Y. Sui, G.Wang, L. Zhang, and M.-H. Yang, "Exploiting spatial-temporal locality of tracking via structured dictionary learning,'' IEEE Trans. Image Process., vol. 27, no. 3, pp. 1282-1296, Mar. 2018.

[55] Y. Sui and L. Zhang, "Visual tracking via locally structured Gaussian process regression,'' IEEE Signal Process. Lett., vol. 22, no. 9, pp. 1331-1335, Sep. 2015.

[56] Y. Sui, Y. Tang, and L. Zhang, "Discriminative low-rank tracking,'' in Proc. IEEE Int. Conf. Comput. Vis., Dec. 2015, pp. 3002-3010.