Sparse representation and learning in visual recognition: Theory and applications

Signal Processing

Volumn 93, Issue 6, 2013, Pages 1408-1425

  Cheng, Hong ^a   Liu, Zicheng ^b   Yang, Lu ^a   Chen, Xuewen ^c  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b MICROSOFT RESEARCH   (United States)

^c WAYNE STATE UNIVERSITY   (United States)

Author keywords

Sparse representation; Sparse subspace learning; Sparsity Induced Similarity; Structured sparsity; Visual recognition

Indexed keywords

SPARSE REPRESENTATION; SPARSITY INDUCED SIMILARITY; STRUCTURED SPARSITIES; SUBSPACE LEARNING; VISUAL RECOGNITION;

ARTIFICIAL INTELLIGENCE; PATTERN RECOGNITION;

LEARNING SYSTEMS;

EID: 84875252662     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2012.09.011     Document Type: Article

References (195)

1. 1 minimization Proceedings of the National Academy of Sciences 100 5 2003 2197
2. E.J. Candes, J.K. Romberg, and T. Tao Stable signal recovery from incomplete and inaccurate measurements Communications on Pure and Applied Mathematics 59 8 2006 1207 1223
3. E. Candes, and T. Tao Near-optimal signal recovery from random projections universal encoding strategies? IEEE Transactions on Information Theory 52 12 2006 5406 5425
4. D. Donoho, I. Drori, Y. Tsaig, J. Starck, Sparse Solution of Underdetermined Linear Equations by Stagewise Orthogonal Matching Pursuit, Department of Statistics, Stanford University, 2006.
5. D. Donoho Compressed sensing IEEE Transactions on Information Theory 52 4 2006 1289 1306
6. E. Candes, and T. Tao Decoding by linear programming IEEE Transactions on Information Theory 51 12 2005 4203 4215
7. K. Huang, S. Aviyente, Sparse Representation for Signal Classification, in: NIPS, 2006.
8. D. Reddy, A. Veeraraghavan, R. Chellappa, P2C2: Programmable Pixel Compressive Camera for High Speed Imaging, in: CVPR, 2011.
9. X. Shu, N. Ahuja, Hybrid compressive sampling via a new total variation TVL1, in: ECCV, vol. 6316, 2010.
10. T. Zhou, D. Tao, and X. Wu Manifold elastic net a unified framework for sparse dimension reduction Data Mining and Knowledge Discovery 22 3 2011 340 371
11. D. Hsu, S. Kakade, J. Langford, T. Zhang, Multi-Label Prediction via Compressed Sensing, Arxiv preprint arXiv:0902.1284.
12. S. Ji, Y. Xue, and L. Carin Bayesian compressive sensing IEEE Transactions on Signal Processing 56 6 2008 2346 2356
13. L. He, H. Chen, and L. Carin Tree-structured compressive sensing with variational Bayesian analysis IEEE Signal Processing Letters 17 3 2010 233 236
14. D.D. Lee, and H.S. Seung Learning the parts of objects by non-negative matrix factorization Nature 401 6755 1999 788 791
15. J. Eggert, E. Korner, Sparse coding and NMF, in: IEEE International Joint Conference on Neural Networks, vol. 4, 2004.
16. J. Yang, Y. Peng, W. Xu, and Q. Dai Ways to sparse representation an overview Science in China Series F Information Sciences 52 2009 695 703
17. T. Poggio, and F. Girosi A sparse representation for function approximation Neural Computation 10 1998 1445 1454
18. J.A. Starzyk, Y. Liu, D. Vogel, Sparse coding in sparse winner networks, in: International Symposium on Neural Networks: Part II - Advances in Neural Networks (ISNN), 2007.
19. J. Wright, Y. Ma, J. Mairal, G. Sapiro, T. Huang, and S. Yan Sparse representation for computer vision and pattern recognition Proceedings of the IEEE 98 6 2010 1031 1044
20. J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma Robust face recognition via sparse representation IEEE Transactions on Pattern Analysis and Machine Intelligence 31 2 2009 210 227
21. X. Shen, Y. Wu, Sparsity model for robust optical flow estimation at motion discontinuities, in: CVPR, 2010.
22. K. Jia, X. Wang, X. Tang, Optical flow estimation using learned sparse model, in: ICCV, 2011.
23. Y. Zheng, J. Gee, Estimation of image bias field with sparsity constraints, in: CVPR, 2010.
24. W. Dong, L. Zhang, G. Shi, Centralized sparse representation for image restoration, in: ICCV, 2011.
25. J.-F. Cai, H. Ji, C. Liu, Z. Shen, Blind motion deblurring from a single image using sparse approximation, in: CVPR, 2009.
26. A. Sankaranarayanan, P. Turaga, R. Baraniuk, R. Chellappa, Compressive acquisition of dynamic scenes, in: ECCV, vol. 6311, 2010.
27. E. Elhamifar, R. Vidal, Sparse subspace clustering, in: CVPR, 2009.
28. H. Lee, R. Grosse, R. Ranganath, A.Y. Ng, Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, in: ICML, 2009.
29. H. Cheng, Z. Liu, J. Yang, Sparsity induced similarity measure for label propagation, in: ICCV, 2009.
30. A. Bruckstein, D. Donoho, and M. Elad From sparse solutions of systems of equations to sparse modeling of signals and images SIAM Review 51 1 2009 34 81
31. E. Candes, and M. Wakin An introduction to compressive sampling IEEE Signal Processing Magazine 25 2 2008 21 30
32. D.L. Donoho For most large underdetermined systems of linear equations the minimal L1-norm solution is also the sparsest solution Communications on Pure and Applied Mathematics 59 6 2006 797 829
33. E.J. Candes The restricted isometry property and its implications for compressed sensing Comptes Rendus Mathematique 346 9C10 2008 589 592
34. S. Chen, D. Donoho, and M. Saunders Atomic decomposition by basis pursuit SIAM Journal on Scientific Computing 20 1 1999 33 61
35. E. Candes, J. Romberg, and T. Tao Robust uncertainty principles exact signal reconstruction from highly incomplete frequency information IEEE Transactions on Information Theory 52 2 2006 489 509
36. S. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky An interior-point method for large-scale L1-regularized least squares IEEE Journal of Selected Topics in Signal Processing 1 4 2007 606 617
37. M. Figueiredo, R. Nowak, and S. Wright Gradient projection for sparse reconstruction application to compressed sensing and other inverse problems IEEE Journal of Selected Topics in Signal Processing 1 4 2007 586 597
38. I. Daubechies, M. Defrise, and C. De Mol An iterative thresholding algorithm for linear inverse problems with a sparsity constraint Communications on Pure and Applied Mathematics 57 11 2004 1413 1457
39. H. Huang, and A. Makur Backtracking-based matching pursuit method for sparse signal reconstruction IEEE Signal Processing Letters 18 7 2011 391
40. Y. Pati, R. Rezaiifar, P. Krishnaprasad, Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition, in: Conference Record of the 27th Asilomar Conference on Signals, Systems and Computers, 1993.
41. J. Tropp, and A. Gilbert Signal recovery from random measurements via orthogonal matching pursuit IEEE Transactions on Information Theory 53 12 2007 4655 4666
42. D. Needell, and R. Vershynin Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit IEEE Journal of Selected Topics in Signal Processing 4 2 2010 310 316
43. D. Needell, and R. Vershynin Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit Foundations of Computational Mathematics 9 3 2009 317 334
44. A. Gilbert, S. Guha, P. Indyk, S. Muthukrishnan, M. Strauss, Near-optimal sparse Fourier representations via sampling, in: Proceedings of the 34th Annual ACM Symposium on Theory of Computing, 2002.
45. A. Gilbert, S. Muthukrishnan, M. Strauss, Improved time bounds for near-optimal sparse Fourier representations, in: Proceedings of SPIE, vol. 5914, 2005.
46. R. Tibshirani Regression shrinkage and selection via the LASSO Journal of the Royal Statistical Society. Series B (Methodological) 1996 267 288
47. S. Mallat, and Z. Zhang Matching pursuits with time-frequency dictionaries IEEE Transactions on Signal Processing 41 12 1993 3397 3415
48. J. Tropp Greed is good algorithmic results for sparse approximation IEEE Transactions on Information Theory 50 10 2004 2231 2242
49. S.S. Chen, D.L. Donoho, and M.A. Saunders Atomic decomposition by basis pursuit SIAM Journal on Scientific Computing 20 1 1998 33 61
50. S. Qian, and D. Chen Signal representation using adaptive normalized Gaussian functions Signal Processing 36 1 1994 1 11
51. D. Needell, and J.A. Tropp CoSaMP Iterative signal recovery from incomplete and inaccurate samples Applied and Computational Harmonic Analysis 26 3 2008 301 321
52. R. Tibshirani Regression shrinkage and selection via the LASSO a retrospective Journal of the Royal Statistical Society Series B (Statistical Methodology) 73 3 2011 273 282
53. H. Zou The adaptive LASSO and its oracle properties Journal of the American Statistical Association 101 476 2006 1418 1429
54. B. Ng, R. Abugharbieh, Generalized group sparse classifiers with application in fMRI brain decoding, in: CVPR, 2011.
55. T. Park, and G. Casella The Bayesian LASSO Journal of the American Statistical Association 103 482 2008 681 686
56. L. Shen, C. Yeo, Intrinsic images decomposition using a local and global sparse representation of reflectance, in: CVPR, 2011.
57. F. Bach Consistency of the group LASSO and multiple kernel learning Journal of Machine Learning Research 9 2008 1179 1225
58. J. Huang, T. Zhang, The Benefit of Group Sparsity, Technical Report, Rutgers University, 2009.
59. M. Stojnic, F. Parvaresh, and B. Hassibi On the reconstruction of block-sparse signals with an optimal number of measurements IEEE Transactions on Signal Processing 57 8 2009 3075 3085
60. M. Yuan, M. Yuan, Y. Lin, and Y. Lin Model selection and estimation in regression with grouped variables Journal of the Royal Statistical Society, Series B 68 2006 49 67
61. A. Rakotomamonjy Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms Signal Processing 91 7 2011 1505 1526
62. L. Daudet, Sparse and structured decomposition of audio signals in overcomplete spaces, in: International Conference on Digital Audio Effects, 2004.
63. A. Majumdar, R. Ward, Classification via group sparsity promoting regularization, in: ICASSP, 2009.
64. J. Huang, X. Huang, D. Metaxas, Learning with dynamic group sparsity, in: ICCV, 2009.
65. S. Zhang, J. Huang, Y. Huang, Y. Yu, H. Li, D. Metaxas, Automatic image annotation using group sparsity, in: CVPR, 2010.
66. Y. Yang, Y. Yang, Z. Huang, H.T. Shen, F. Nie, Tag localization with spatial correlations and joint group sparsity, in: CVPR, 2011.
67. J. Huang, T. Zhang, D. Metaxas, Learning with structured sparsity, in: ICML, 2009.
68. J. Huang, T. Zhang, and D. Metaxas Learning with structured sparsity Journal of Machine Learning Research 12 2011 3371 3412
69. E. Elhamifar, R. Vidal, Robust classification using structured sparse representation, in: CVPR, 2011.
70. K. Yu, T. Zhang, Y. Gong, Nonlinear learning using local coordinate coding, in: NIPS, 2009.
71. S. Roweis, and L. Saul Nonlinear dimensionality reduction by locally linear embedding Science 290 5500 2000 2323
72. K. Yu, T. Zhang, High dimensional nonlinear learning using local coordinate coding, in: ICML, 2009.
73. J. Yang, K. Yu, Y. Gong, T. Huang, Linear spatial pyramid matching using sparse coding for image classification, in: CVPR, 2009.
74. S. Gao, I. Tsang, L.-T. Chia, Kernel sparse representation for image classification and face recognition, in: ECCV, vol. 6314, 2010.
75. R. Sivalingam, D. Boley, V. Morellas, N. Papanikolopoulos, Tensor sparse coding for region covariances, in: ECCV, vol. 6314, 2010.
76. S. Ji, D. Dunson, and L. Carin Multitask compressive sensing IEEE Transactions on Signal Processing 57 1 2009 92 106
77. Y. Qi, D. Liu, D. Dunson, L. Carin, Multi-task compressive sensing with Dirichlet process priors, in: ICML, 2008.
78. L. He, and L. Carin Exploiting structure in wavelet-based Bayesian compressive sensing IEEE Transactions on Signal Processing 57 9 2009 3488 3497
79. M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro, L. Carin, Non-parametric Bayesian dictionary learning for sparse image representations, in: NIPS, 2009.
80. M. Chen, J. Silva, J. Paisley, C. Wang, D. Dunson, and L. Carin Compressive sensing on manifolds using a nonparametric mixture of factor analyzers algorithm and performance bounds IEEE Transactions on Signal Processing 58 12 2010 6140 6155
81. M. Zhou, H. Chen, J. Paisley, L. Ren, L. Li, Z. Xing, D. Dunson, G. Sapiro, and L. Carin Nonparametric Bayesian dictionary learning for analysis of noisy and incomplete images IEEE Transactions on Image Processing 21 1 2012 130 144
82. X. Ding, L. He, and L. Carin Bayesian robust principal component analysis IEEE Transactions on Image Processing 20 12 2011 3419 3430
83. E. Elhamifar, R. Vidal, Clustering disjoint subspaces via sparse representation, in: ICASSP, 2010.
84. G. Liu, Z. Lin, Y. Yu, Robust subspace segmentation by low-rank representation, in: ICML, 2010.
85. B. Nasihatkon, R. Hartley, Graph connectivity in sparse subspace clustering, in: CVPR, 2011.
86. L. Zhang, P. Zhu, Q. Hu, D. Zhang, A linear subspace learning approach via sparse coding, in: ICCV, 2011.
87. R. Vidal Subspace clustering IEEE Signal Processing Magazine 28 2 2011 52 68
88. Y. Liu, F. Wu, Z. Zhang, Y. Zhuang, S. Yan, Sparse representation using nonnegative curds and whey, in: CVPR, 2010.
89. Y. Gao, A. Choudhary, G. Hua, A nonnegative sparsity induced similarity measure with application to cluster analysis of spam images, in: ICASSP, 2010.
90. C. Zhang, J. Liu, Q. Tian, C. Xu, H. Lu, S. Ma, Image classification by non-negative sparse coding, low-rank and sparse decomposition, in: CVPR, 2011.
91. X. Mei, H. Ling, D. Jacobs, Sparse representation of cast shadows via L1-regularized least squares, in: ICCV, 2009.
92. R. He, W.-S. Zheng, B.-G. Hu, X.-W. Kong, Nonnegative sparse coding for discriminative semi-supervised learning, in: CVPR, 2011.
93. S. Boyd, and L. Vandenberghe Convex Optimization 2004 Cambridge University Press
94. R. Andersen, Modern Methods for Robust Regression, no. 152, Sage Publications, 2008.
95. P. Huber Robust regression asymptotics, conjectures and Monte Carlo Annals of Statistics 1 5 1973 799 821
96. M. Yang, L. Zhang, J. Yang, D. Zhang, Robust sparse coding for face recognition, in: CVPR, 2011.
97. B. Liu, L. Yang, J. Huang, P. Meer, L. Gong, C. Kulikowski, Robust and fast collaborative tracking with two stage sparse optimization, in: ECCV, vol. 6314, 2010.
98. B. Liu, J. Huang, L. Yang, C. Kulikowski, Robust tracking using local sparse appearance model and K-selection, in: CVPR, 2011.
99. M. Yang, L. Zhang, Gabor feature based sparse representation for face recognition with Gabor occlusion dictionary, in: ECCV, vol. 6316, 2010.
100. M. Yang, L. Zhang, X. Feng, D. Zhang, Fisher discrimination dictionary learning for sparse representation, in: ICCV, 2011.
101. C. Peng, and J. Li Fast sparse representation model for L1-norm minimisation problem Electronics Letters 48 3 2012 162 164
102. P. Viola, and M.J. Jones Robust real-time face detection International Journal of Computer Vision 57 2004 137 154
103. S. Paisitkriangkrai, C. Shen, J. Zhang, Efficiently training a better visual detector with sparse eigenvectors, in: CVPR, 2009.
104. J.-B. Huang, M.-H. Yang, Fast sparse representation with prototypes, in: CVPR, 2010.
105. N. Naikal, A.Y. Yang, S. Shankar Sastry, Informative feature selection for object recognition via sparse PCA, in: ICCV, 2011.
106. K. Sohn, D.Y. Jung, H. Lee, A.O. Hero, Efficient learning of sparse, distributed, convolutional feature representations for object recognition, in: ICCV, 2011.
107. N. Dalal, B. Triggs, Histograms of oriented gradients for human detection, in: CVPR, vol. 1, 2005.
108. D. Lowe Distinctive image features from scale-invariant keypoints International Journal of Computer Vision 60 2 2004 91 110
109. H. Cheng, Z. Liu, N. Zheng, J. Yang, A deformable local image descriptor, in: CVPR, 2008.
110. H. Zou, T. Hastie, and R. Tibshirani Sparse principal component analysis Journal of Computational and Graphical Statistics 15 2 2006 265 286
111. L. Wang, H. Cheng, Robust sparse PCA via weighted elastic net, in: Chinese Conference on Pattern Recognition, 2012.
112. J. Yang, K. Yu, T. Huang, Supervised translation-invariant sparse coding, in: CVPR, 2010.
113. D. Krishnan, T. Tay, R. Fergus, Blind deconvolution using a normalized sparsity measure, in: CVPR, 2011.
114. K. Yu, Y. Lin, J. Lafferty, Learning image representations from the pixel level via hierarchical sparse coding, in: CVPR, 2011.
115. Y. Li, C. Fermuller, Y. Aloimonos, H. Ji, Learning shift-invariant sparse representation of actions, in: CVPR, 2010.
116. J. Morel, and G. Yu ASIFT a new framework for fully affine invariant image comparison SIAM Journal on Imaging Sciences 2 2 2009 438 469
117. N. Kulkarni, B. Li, Discriminative affine sparse codes for image classification, in: CVPR, 2011.
118. X. Li, T. Jia, H. Zhang, Expression-insensitive 3D face recognition using sparse representation, in: CVPR, 2009.
119. P. Nagesh, B. Li, A compressive sensing approach for expression-invariant face recognition, in: CVPR, 2009.
120. B. Olshausen, and D. Field Sparse coding with an overcomplete basis set a strategy employed by V1? Vision Research 37 23 1997 3311 3325
121. K. Kreutz-Delgado, J. Murray, B. Rao, K. Engan, T. Lee, and T. Sejnowski Dictionary learning algorithms for sparse representation Neural Computation 15 2 2003 349 396
122. J. Mairal, F. Bach, J. Ponce, G. Sapiro, Online dictionary learning for sparse coding, in: ICML, 2009.
123. J. Shi, X. Ren, G. Dai, J. Wang, Z. Zhang, A non-convex relaxation approach to sparse dictionary learning, in: CVPR, 2011.
124. Y. Cong, J. Yuan, J. Liu, Sparse reconstruction cost for abnormal event detection, in: CVPR, 2011.
125. C.-K. Chiang, C.-H. Duan, S.-H. Lai, S.-F. Chang, Learning component-level sparse representation using histogram information for image classification, in: ICCV, 2011.
126. B. Zhao, L. Fei-Fei, E. Xing, Online detection of unusual events in videos via dynamic sparse coding, in: CVPR, 2011.
127. I. Ramirez, P. Sprechmann, G. Sapiro, Classification and clustering via dictionary learning with structured incoherence and shared features, in: CVPR, 2010.
128. Z. Jiang, Z. Lin, L. Davis, Learning a discriminative dictionary for sparse coding via label consistent K-SVD, in: CVPR, 2011.
129. Z. Jiang, G. Zhang, L.S. Davis, Submodular dictionary learning for sparse coding, in: CVPR, 2012.
130. D. Pham, S. Venkatesh, Joint learning and dictionary construction for pattern recognition, in: CVPR, 2008.
131. J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman, Non-local sparse models for image restoration, in: ICCV, 2009.
132. W. Dong, X. Li, L. Zhang, G. Shi, Sparsity-based image denoising via dictionary learning and structural clustering, in: CVPR, 2011.
133. J. Yang, Z. Wang, Z. Lin, X. Shu, T. Huang, Bilevel sparse coding for coupled feature spaces, in: CVPR, 2012.
134. T. Zhang, B. Ghanem, S. Liu, N. Ahuja, Robust visual tracking via multi-task sparse learning, in: CVPR, 2012.
135. J. Sivic, A. Zisserman, Video Google: a text retrieval approach to object matching in videos, in: ICCV, 2003.
136. F. Jurie, B. Triggs, Creating efficient codebooks for visual recognition, in: ICCV, vol. 1, 2005.
137. Y. Jiang, and C. Ngo Visual word proximity and linguistics for semantic video indexing and near-duplicate retrieval Computer Vision and Image Understanding 113 3 2009 405 414
138. J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman, Supervised Dictionary Learning, Arxiv preprint 0809.3083.
139. Q. Qiu, Z. Jiang, R. Chellappa, Sparse dictionary-based representation and recognition of action attributes, in: ICCV, 2011.
140. D. Lowe Similarity metric learning for a variable-kernel classifier Neural Computation 7 1 1995 72 85
141. B. Cheng, J. Yang, S. Yan, Y. Fu, and T. Huang Learning with l1-graph for image analysis IEEE Transactions on Image Processing 19 4 2010 858 866
142. H. Liu, F. Sun, Visual tracking using sparsity induced similarity, in: ICPR, 2010.
143. H. Wang, H. Huang, C. Ding, Image categorization using directed graphs, in: ECCV, vol. 6313, 2010.
144. S. Lazebnik, C. Schmid, J. Ponce, Beyond Bags of Features: Spatial pyramid matching for recognizing natural scene categories, in: CVPR, vol. 2, 2006.
145. S. Gao, I. Tsang, L.-T. Chia, P. Zhao, Local features are not lonely - Laplacian sparse coding for image classification, in: CVPR, 2010.
146. D. Dai, W. Yang, T. Wu, Three-layer spatial sparse coding for image classification, in: ICPR, 2010.
147. X.-T. Yuan, S. Yan, Visual classification with multi-task joint sparse representation, in: CVPR, 2010.
148. S. Gao, L.-T. Chia, I.-H. Tsang, Multi-layer group sparse coding - for concurrent image classification and annotation, in: CVPR, 2011.
149. H. Zhang, J. Yang, Y. Zhang, N.M. Nasrabadi, T.S. Huang, Close the loop: joint blind image restoration and recognition with sparse representation prior, in: ICCV, 2011.
150. J. Yang, K. Yu, T. Huang, Efficient highly over-complete sparse coding using a mixture model, in: ECCV, vol. 6315, 2010.
151. Y. Hong, Q. Li, J. Jiang, Z. Tu, Learning a mixture of sparse distance metrics for classification and dimensionality reduction, in: ICCV, 2011.
152. Y. Hu, A. Mian, R. Owens, Sparse approximated nearest points for image set classification, in: CVPR, 2011.
153. S. Paisitkriangkrai, C. Shen, A. van den Hengel, Sharing features in multi-class boosting via group sparsity, in: CVPR, 2012.
154. A. Vedaldi, A. Zisserman, Sparse kernel approximations for efficient classification and detection, in: CVPR, 2012.
155. P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan Object detection with discriminatively trained part-based models IEEE Transactions on Pattern Analysis and Machine Intelligence 32 9 2010 1627 1645
156. D.D. Lee, and H.S. Seung Learning the parts of objects by non-negative matrix factorization Nature 401 21 1999 788 791
157. N. Guan, D. Tao, Z. Luo, and B. Yuan Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent IEEE Transactions on Image Processing 20 7 2011 2030 2048
158. P. Hoyer, Non-negative sparse coding, in: IEEE Workshop on Neural Networks for Signal Processing, 2002.
159. L. Shang, C. Zhou, Y. Gu, Y. Zhang, Face recognition using the feature fusion technique based on LNMF and NNSC algorithms, in: Advanced Intelligent Computing Theories and Applications, 2010.
160. D. Cai, X. He, X. Wu, J. Han, Non-negative matrix factorization on manifold, in: IEEE International Conference on Data Mining, 2008.
161. N. Guan, D. Tao, Z. Luo, B. Yuan, NeNMF: An optimal gradient method for non-negative matrix factorization, IEEE Transactions on Signal Processing, 10.1109/TSP.2012.2190406, in press.
162. X. Tian, D. Tao, Y. Rui, Sparse transfer learning for interactive video search reranking, ACM Transactions on Multimedia Computing, Communications, and Applications, 10.1145/2240136.2240139, in press.
163. B. Geng, C. Xu, D. Tao, L. Yang, X.S. Hua, Ensemble manifold regularization, in: CVPR, 2009.
164. N. Guan, D. Tao, Z. Luo, J. Shawe-Taylor, MahNMF: Manhattan Non-Negative Matrix Factorization, Arxiv preprint arXiv:1207.3438v1.
165. N. Guan, D. Tao, Z. Luo, and B. Yuan Non-negative patch alignment framework IEEE Transactions on Neural Networks 22 8 2011 1218 1230
166. E.J. Candes, and B. Recht Exact matrix completion via convex optimization Foundations of Computational Mathematics 9 2009 717 772
167. T. Zhou, D. Tao, GoDec: Randomized low-rank & sparse matrix decomposition in noisy case, in: ICML, 2011.
168. Y. Peng, A. Ganesh, J. Wright, W. Xu, Y. Ma, RASL: robust alignment by sparse and low-rank decomposition for linearly correlated images, in: CVPR, 2010.
169. X. Tan, Y. Li, J. Liu, L. Jiang, Face liveness detection from a single image with sparse low rank bilinear discriminative model, in: ECCV, vol. 6316, 2010.
170. X. Shu, N. Ahuja, Imaging via three-dimensional compressive sampling (3DCS), in: ICCV, 2011.
171. G. Liu, S. Yan, Latent low-rank representation for subspace segmentation and feature extraction, in: ICCV, 2011.
172. l 1-norm by dynamic systems, Image and Vision Computing, 10.1016/j.imavis.2012.06.012
173. l 1 norm Visual Computer 2012 1 11
174. D. Cai, H. Bao, X. He, Sparse concept coding for visual analysis, in: CVPR, 2011.
175. L. Benoit, J. Mairal, F. Bach, J. Ponce, Sparse image representation with epitomes, in: CVPR, 2011.
176. K. Yu, Y. Lin, J. Lafferty, Learning image representations from the pixel level via hierarchical sparse coding, in: CVPR, 2011.
177. C. Wang, S. Yan, L. Zhang, H.-J. Zhang, Multi-label sparse coding for automatic image annotation, in: CVPR, 2009.
178. L. Jacques, L. Duval, C. Chaux, and G. Peyre A panorama on multiscale geometric representations, intertwining spatial, directional and frequency selectivity Signal Processing 91 12 2011 2699 2730
179. M. Song, C. Chen, J. Bu, and T. Sha Image-based facial sketch-to-photo synthesis via online coupled dictionary learning Information Sciences 193 0 2012 233 246
180. Y. Lin, M. Song, D.T.P. Quynh, Y. He, and C. Chen Sparse coding for flexible, robust 3D facial-expression synthesis IEEE Computer Graphics and Applications 32 2 2012 76 88
181. Y. Yang, N. Zheng, Y. Liu, S. Du, Y. Su, and Y. Nishio Expression transfer for facial sketch animation Signal Processing 91 11 2011 2465 2477
182. J. Yu, J. Cheng, and D. Tao Interactive cartoon reusing by transfer learning Signal Processing 92 9 2012 2147 2158
183. W. Li, J. Zhang, and Q.-H. Dai Video denoising using shape-adaptive sparse representation over similar spatio-temporal patches Signal Processing Image Communication 26 4-5 2011 250 265
184. Y. He, T. Gan, W. Chen, and H. Wang Multi-stage image denoising based on correlation coefficient matching and sparse dictionary pruning Signal Processing 92 1 2012 139 149
185. S. Ikehata, D. Wipf, Y. Matsushita, K. Aizawa, Robust photometric stereo using sparse regression, in: CVPR, 2012.
186. I. Khalidov, J. Fadili, F. Lazeyras, D.V.D. Ville, and M. Unser Activelets wavelets for sparse representation of hemodynamic responses Signal Processing 91 12 2011 2810 2821
187. J. Aelterman, H.Q. Luong, B. Goossens, A. Pizurica, and W. Philips Augmented lagrangian based reconstruction of non-uniformly sub-Nyquist sampled MRI data Signal Processing 91 12 2011 2731 2742
188. A. Majumdar, and R.K. Ward Compressed sensing of color images Signal Processing 90 12 2010 3122 3127
189. X. Bi, X.-D. Chen, Y. Zhang, and B. Liu Image compressed sensing based on wavelet transform in contourlet domain Signal Processing 91 5 2011 1085 1092
190. A. Colaco, A. Kirmani, G. Howland, J. Howell, V. K. Goyal, Compressive depth map acquisition using a single photon-counting detector-parametric signal processing meets sparsity, in: CVPR, 2012.
191. N. Guan, D. Tao, Z. Luo, B. Yuan, Online nonnegative matrix factorization with robust stochastic approximation, IEEE Transactions on Neural Networks and Learning Systems, 10.1109/TNNLS.2012.2197827, in press.
192. L. Zhuang, H. Gao, Z. Lin, Y. Ma, N. Yu, Non-negative low rank and sparse graph for semi-supervised learning, in: CVPR, 2012.
193. R. Rigamonti, M. Brown, V. Lepetit, Are sparse representations really relevant for image classification?, in: CVPR, 2011.
194. Q. Shi, A. Eriksson, A. van den Hengel, C. Shen, Is face recognition really a compressive sensing problem?, in: CVPR, 2011.
195. L. Zhang, M. Yang, X. Feng, Sparse representation or collaborative representation: which helps face recognition? in: ICCV, 2011.