Wu Y, Wu B, Liu J, et al. Probabilistic tracking on riemannian manifolds[C]. The 19th Int Conf on Pattern Recognition. Florida, 2008: 1-4.
[2]
Kwon J H, Lee K M, Par F C. Visual tracking via geometric particle filtering on the affine group with optimal importance functions[C]. IEEE Conf on Computer Vision and Pattern Recognition. Seoul, 2009: 991-998.
(Zhu M Q,Wang Z L, Chen Z H. Visual tracking algorithm based on grey prediction model and particle filter[J]. Control and Decision, 2012, 27(1): 53-57.)
[5]
Liu Y P, Li G W, Shi Z L. Covariance tracking via geometric particle filtering[J]. J on Advances in Signal Processing, 2010: 1-9.
[6]
Wu Y, Cheng J, Wang J Q. Real-time probabilistic covariance tracking with efficient model update[J]. IEEE Trans on Image Processing, 2012, 21(5): 2824-2837.
[7]
Khan Z H, Gu I Y H. Tracking visual and infrared objects using joint riemannian manifold appearance and affine shape modeling[C]. IEEE Int Conf on Computer Vision Workshops. Gothenburg, 2011: 1847-1854.
[8]
Wang Q, Xu W L. Object tracking via partial least squares analysis[J]. IEEE Trans on Image Processing, 2012, 21(10): 4454-4465.
(Chen Z M, Bo Y M, Wu P L, et al. Novel particle filter algorithm based on adaptive particle swarm optimization and its application to radar target tracking[J]. Control and Decision, 2013, 28(2): 193-200.)
[11]
Porikli F, Tuzel O, Meer P. Covariance tracking using model update based on Lie algebra[C]. IEEE Computer Society Conf on Computer Vision and Pattern Recognition. New York, 2006: 728-735.
[12]
Li G W, Liu Y P, Yin J. Target tracking with feature covariance based on an improved lie group structure[J]. Chinese J of Scientific Instrument, 2010, 31(1): 111-116.
[13]
Khan Z H, Gu I Y. Bayesian online learning on riemannian manifolds using a dual model with applications to video object tracking[C]. IEEE Int Conf on Computer Vision Workshops. Gothenburg, 2011: 1042-1409.
[14]
Wu Y, Wu B, Liu J, et al. Probabilistic tracking on riemannian manifolds[C]. The 19th Int Conf on Pattern Recognition. Florida, 2008: 1-4.
[15]
Ross D, Lim J, Lim R S, et al. Incremental learning for robust visual tracking[J]. Int J of Computer Vision, 2008, 77(1): 125-141.
[16]
Cai H, Li N, Zhao H J. The tracking approach for small target with complex background based on spectral features[C]. The 8th IEEE Int Symposium on Instrumentation and Control Technology. London, 2012: 55-60.
(Lu W, Cai J J. Object tracking using robust subspace learning in particle filter[J]. Application Research of Computers, 2011, 28(9): 3579-3584.)
[19]
Roman R, Nicole K. Overview and recent advances in partial least squares[J]. Latent Structures Feature Selection, 2006, 3940: 34-51.
[20]
Srinivasan B V, Zotkin D N. Duraiswami R. A partial least squares framework for speaker recognition[C]. The IEEE Int Conf on Acoustics, Speech and Signal Processing. Prague, 2011: 5276-5279.
[21]
Berger M. A panoramic view of Riemannian geometry[M]. Berlin: Springer, 2003: 161-232.
[22]
Hall B C. Lie algebras and representations: An elementary introduction[M]. NewYork: Springer, 2003: 3-58.
