S. Zhang, H. Yao, X. Sun, and X. Lu, Sparse coding based visual tracking: Review and experimental comparison, Pattern Recognition, vol.46, issue.7, pp.1772-1788, 2013.
DOI : 10.1016/j.patcog.2012.10.006

S. Zhang, H. Zhou, F. Jiang, and X. Li, Robust Visual Tracking Using Structurally Random Projection and Weighted Least Squares, IEEE Transactions on Circuits and Systems for Video Technology, vol.25, issue.11
DOI : 10.1109/TCSVT.2015.2406194

M. Belkin and P. Niyogi, Laplacian eigenmaps and spectral techniques for embedding and clustering, Proc. NIPS, pp.585-591, 2001.

X. Zhang, Y. Yang, L. C. Jiao, and F. Dong, Manifold-constrained coding and sparse representation for human action recognition, Pattern Recognition, vol.46, issue.7, pp.1819-1831, 2013.
DOI : 10.1016/j.patcog.2012.10.011

M. Belkin, Problems of learning on manifolds, 2003.

S. Zhang, S. Kasiviswanathan, P. C. Yuen, and M. T. Harandi, Online dictionary learning on symmetric positive definite manifolds with vision applications, Proc. AAAI, pp.3165-3173, 2015.

D. D. Lee and H. S. Seung, Learning the parts of objects by non-negative matrix factorization, Nature, vol.401, issue.6755, pp.788-791, 1999.

Y. Wu, B. Shen, and H. Ling, Visual Tracking via Online Nonnegative Matrix Factorization, IEEE Transactions on Circuits and Systems for Video Technology, vol.24, issue.3, pp.374-383, 2014.
DOI : 10.1109/TCSVT.2013.2278199
URL : http://www.dabi.temple.edu/~hbling/publication/nmf-tracking-13csvt.pdf

H. Zhang, A. Berg, M. Maire, and J. Malik, SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.2126-2136, 2006.
DOI : 10.1109/CVPR.2006.301

L. Bottou and V. N. Vapnik, Local Learning Algorithms, Neural Computation, vol.2, issue.6, pp.888-900, 1992.
DOI : 10.1162/neco.1989.1.2.281

]. C. Cortes and V. Vapnik, Support-vector networks, Machine Learning, vol.1, issue.3, pp.273-297, 1995.
DOI : 10.1007/BF00994018

J. Lim, D. Ross, R. Lin, and M. Yang, Incremental learning for visual tracking, Proc. NIPS, pp.793-800, 2005.

S. Zhang, H. Zhou, H. Yao, Y. Zhang, K. Wang et al., Adaptive NormalHedge for robust visual tracking, Signal Processing, vol.110, pp.132-142, 2015.
DOI : 10.1016/j.sigpro.2014.08.027

A. Adam, E. Rivlin, and I. Shimshoni, Robust Fragments-based Tracking using the Integral Histogram, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.798-805, 2006.
DOI : 10.1109/CVPR.2006.256

H. Grabner, M. Grabner, and H. Bischof, Real-time tracking via online boosting, Proc. BMVC, pp.47-56, 2006.
DOI : 10.5244/c.20.6
URL : http://www.bmva.org/bmvc/2006/papers/033.pdf

H. Grabner, C. Leistner, and H. Bischof, Semisupervised on-line boosting for robust tracking, Proc. ECCV, pp.234-247, 2008.

J. Kwon and K. M. Lee, Visual tracking decomposition, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.1269-1276, 2010.
DOI : 10.1109/CVPR.2010.5539821
URL : http://cv.snu.ac.kr/publication/conf/2010/VTD_CVPR2010.pdf

B. Babenko, M. C. Yang, and S. Belongie, Visual tracking with online multiple instance learning, Proc. CVPR, pp.983-990, 2009.

B. Babenko, M. C. Yang, and S. Belongie, Robust Object Tracking with Online Multiple Instance Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.8, pp.1619-1632, 2011.
DOI : 10.1109/TPAMI.2010.226
URL : http://faculty.ucmerced.edu/mhyang/papers/pami11b.pdf

K. Zhang, L. Zhang, and M. H. Yang, Real-Time Compressive Tracking, Proc. ECCV, pp.864-877, 2012.
DOI : 10.1007/978-3-642-33712-3_62
URL : http://faculty.ucmerced.edu/mhyang/papers/eccv12_ct.pdf

E. G. Learned-miller and L. S. Lara, Distribution fields for tracking, Proc. CVPR, pp.1910-1917, 2012.

E. Candes, J. Romberg, and T. Tao, Stable signal recovery from incomplete and inaccurate measurements, Communications on Pure and Applied Mathematics, vol.7, issue.8, pp.1207-1223, 2006.
DOI : 10.1017/CBO9780511804441

D. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, pp.1289-1306, 2006.
DOI : 10.1109/TIT.2006.871582
URL : https://hal.archives-ouvertes.fr/inria-00369486

B. Liu, L. Yang, J. Huang, P. Meer, L. Gong et al., Robust and Fast Collaborative Tracking with Two Stage Sparse Optimization, Proc. ECCV, pp.624-637, 2010.
DOI : 10.1007/978-3-642-15561-1_45

S. Zhang, H. Yao, H. Zhou, X. Sun, and S. Liu, Robust visual tracking based on online learning sparse representation, Neurocomputing, vol.100, pp.31-40, 2013.
DOI : 10.1016/j.neucom.2011.11.031

S. Zhang, H. Yao, X. Sun, and S. Liu, Robust Visual Tracking Using an Effective Appearance Model Based on Sparse Coding, ACM Transactions on Intelligent Systems and Technology, vol.3, issue.3, pp.1-18, 2012.
DOI : 10.1145/2168752.2168757

X. Mei and H. Ling, Robust visual tracking using L1 minimization, Proc. ICCV, pp.1436-1443, 2009.

X. Mei and H. Ling, Robust visual tracking and vehicle classification via sparse representation, IEEE Trans. Pattern Anal. Mach. Intell, vol.33, issue.11, pp.2259-2272, 2011.

D. Wang, H. Lu, and M. H. Yang, Least Soft-Threshold Squares Tracking, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.2371-2378, 2013.
DOI : 10.1109/CVPR.2013.307

H. Liu, M. Yuan, F. Sun, and J. Zhang, Spatial Neighborhood-Constrained Linear Coding for Visual Object Tracking, IEEE Transactions on Industrial Informatics, vol.10, issue.1, pp.469-480, 2014.
DOI : 10.1109/TII.2013.2247613

C. Ding, T. Li, and M. I. Jordan, Convex and Semi-Nonnegative Matrix Factorizations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.1, pp.45-55, 2010.
DOI : 10.1109/TPAMI.2008.277
URL : http://ranger.uta.edu/~chqding/papers/Ding-Li-Jordan.pdf

N. Wang, J. Wang, and D. C. Yeung, Online Robust Non-negative Dictionary Learning for Visual Tracking, 2013 IEEE International Conference on Computer Vision, pp.657-664, 2013.
DOI : 10.1109/ICCV.2013.87
URL : http://research.microsoft.com/en-us/um/people/jingdw/pubs/ICCV13-SparseTracker.pdf

C. Qian, Y. Zhuang, and Z. Xu, Visual tracking with structural appearance model based on extended incremental non-negative matrix factorization, Neurocomputing, vol.136, pp.327-336, 2014.
DOI : 10.1016/j.neucom.2013.12.025

H. Zhang, S. Hu, X. Zhang, and L. Luo, Visual Tracking via Constrained Incremental Non-negative Matrix Factorization, IEEE Signal Processing Letters, vol.22, issue.9, pp.1350-1353, 2015.
DOI : 10.1109/LSP.2015.2404856

A. Levinshtein, A. Stere, K. Kutulakos, D. Fleet, S. Dickinson et al., TurboPixels: Fast Superpixels Using Geometric Flows, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.12, pp.2290-2297, 2009.
DOI : 10.1109/TPAMI.2009.96
URL : http://www.cim.mcgill.ca/~shape/publications/pami09.pdf

R. Krishnapuram and J. Keller, A possibilistic approach to clustering, IEEE Transactions on Fuzzy Systems, vol.1, issue.2, pp.98-110, 1993.
DOI : 10.1109/91.227387

J. Wang, J. Yang, K. Yu, F. Lv, T. Huang et al., Localityconstrained linear coding for image classification, Proc. CVPR, pp.3360-3367, 2010.
DOI : 10.1109/cvpr.2010.5540018

S. Lazebnik, C. Schmid, and J. Ponce, Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.2169-2178, 2006.
DOI : 10.1109/CVPR.2006.68
URL : https://hal.archives-ouvertes.fr/inria-00548585

Y. Wu, J. Lim, and M. C. Yang, Online Object Tracking: A Benchmark, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.2411-2418, 2013.
DOI : 10.1109/CVPR.2013.312
URL : http://faculty.ucmerced.edu/mhyang/papers/cvpr13_benchmark.pdf

W. Zhong, H. Lu, and M. Yang, Robust object tracking via sparsitybased collaborative model, Proc. CVPR, pp.1838-1845, 2012.

T. B. Dinh, N. Vo, and G. Medioni, Context tracker: Exploring supporters and distracters in unconstrained environments, CVPR 2011, pp.1177-1184, 2011.
DOI : 10.1109/CVPR.2011.5995733

Z. Kalal, J. Matas, and K. Mikolajczyk, P-N learning: Bootstrapping binary classifiers by structural constraints, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.49-56, 2010.
DOI : 10.1109/CVPR.2010.5540231
URL : http://info.ee.surrey.ac.uk/Personal/Z.Kalal/Publications/2010_cvpr.pdf

S. Hare, A. Saffari, and P. H. Torr, Struck: Structured output tracking with kernels, Proc. ICCV, pp.263-270, 2011.
DOI : 10.1109/iccv.2011.6126251
URL : http://www.ymer.org/papers/files/2011-Struck.pdf

K. Zhang, L. Zhang, Q. Liu, D. Zhang, and M. C. Yang, Fast Visual Tracking via Dense Spatio-temporal Context Learning, Proc. ECCV, pp.127-141, 2014.
DOI : 10.1007/978-3-319-10602-1_9