[1] Cui X W, Wu Q Z, Jiang P, et al. Affine-invariant target tracking based on subspace representation[J]. Infrared and Laser Engineering, 2015, 44(2):769-774. (in Chinese)
[2] Comaniciu D, Ramesh V, Meer P. Kernel-based object tracking[J]. IEEE Trans. Pattern Anal Mach Intell, 2003, 25(5):564-577.
[3] Yang Y F, Tian Y, Yang F, et al. Tracking of infrared small-target based on improved Mean-Shift algorithm[J]. Infrared and Laser Engineering, 2014, 43(7):2164-2169. (in Chinese)
[4] Rangarajan A, Chui H, Mjolsness E. A new distance measure for non-rigid image matching[C]//Energy Minimization Methods in CVPR, 1999:237-252.
[5] Cazzanti L, Gupta M. Information-theoretic and set-theoretic similarity[C]//IEEE Int Conf on Symposium on Information Theory, 2006:1836-1840.
[6] Cao W, Zhu M, He B G, et al. Overview of target tracking technology[J]. Chinese Optics, 2014, 7(3):365-372. (in Chinese)
[7] Chen F, Wang Q, Wang S, et al. Object tracking via appearance modeling and sparse representation[J]. Image Vis Comput, 2011, 29(11):787-796.
[8] Yang C, Duraiswami R, Davis L. Efficient mean-shift tracking via a new similarity measure[C]//IEEE Conf on Computer Vision and Pattern Recognition, 2005:176-183.
[9] Elgammal A, Duraiswami R, Davis L. Probabilistic tracking in joint feature-spatial spaces[C]//IEEE Conf on Computer Vision and Pattern Recognition, 2003:781-788.
[10] Viola P, W M, W III. Alignment by maximization of mutual information[J]. Int J Comput Vision, 1997, 24(2):137-154.
[11] Hero A, Ma B, Michel O, et al. Applications of entropic spanning graphs[J]. IEEE Signal Proc Magazine, 2002, 19(5):85-95.
[12] Garcia J A, Valdivia J F, Vidal X R F, et al. Information theoretic measure for visual target distinctness[J]. IEEE Trans Pattern Anal Mach Intell, 2001, 23(4):362-383.
[13] Yao Z, Lai Z, Liu W. A symmetric KL divergence based spatiogram similarity measure[C]//Int Conf on Image Processing, 2011:193-196.
[14] Cootes T, Taylor C, Cooper D, et al. Active shape models:Their training and application[J]. Comp Vis Ima Unders, 1995, 61(1):38-59.
[15] Sclaroff S, Pentland A P. Model matching for correspondence and recognition[J]. IEEE Trans Patt Anal Mach Intell, 1995, 17(6):545-561.
[16] Wang K, Zhao L, Li R. Fisheye omnidirectional camera calibration-Pinhole or spherical model[C]//IEEE Conf on Robotics and Biomimetics, 2014:873-877.
[17] Xiao Z Z, Qichoo C, Anand A, et al. Measurement of large deformation by digital image correlation method based on seed points[J]. Optics and Precision Engineering, 2011, 19(9):2277-2282.
[18] Bras S, Izadi M, Silvestre C, et al. Nonlinear observer for 3D rigid body motion[C]//IEEE Conf on Decision and Control, 2013:2588-2593.
[19] Zhao L R, Zhu W, Cao Y G, et al. Application of improved SURF algorithm to feature matching[J]. Optics and Precision Engineering, 2013, 21(12):3263-3271. (in Chinese)
[20] Smith S M, Brady J M. SUSAN-a new approach to low level image processing[J]. Int J Comput Vision, 1997, 23(1):45-78.
[21] Xu J J. Fast image registration method based on Harris and SIFT algorithm[J]. Chinese Optics, 2015, 8(4):574-579. (in Chinese)
[22] Kriegel H P, Kroger P, Sander J, et al. Density-based clustering[J]. Data Mining Knowl Discov, 2011, 1(3):231-240.
[23] Grabner H, Bischof H. On-line boosting and vision[C]//IEEE Conf on Computer Vision and Pattern Recognition, 2006:260-267.
[24] Wu Y, Lim J, Yang M H. Online object tracking:a benchmark[C]//IEEE Conf on Computer Vision and Pattern Recognition, 2013:2411-2418.
[25] Wang X, Ma X, Grimson E. Unsupervised activity perception in crowded and complicated scenes using hierarchical Bayesian models[J]. IEEE Trans Pattern Anal Mach Intell, 2009, 31(3):539-555.