PCA-based dictionary building for accurate facial expression recognition via sparse representation

Journal of Visual Communication and Image Representation - Tập 25 Số 5 - Trang 1082-1092 - 2014
Mohsen Mohammadi1, Emad Fatemizadeh1, Mohammad H. Mahoor2
1Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
2Department of Electrical and Computer Engineering, University of Denver, Co, USA

Tóm tắt

Từ khóa


Tài liệu tham khảo

Ekman, 1971, Constants across cultures in the face and emotion, J. Personality Social Psychol., 17, 124, 10.1037/h0030377

Cohen, 2003, Facial expression recognition from video sequences: temporal and static modeling, Comput. Vision Image Underst., 91, 160, 10.1016/S1077-3142(03)00081-X

Maronidis, 2011, Improving subspace learning for facial expression recognition using person dependent and geometrically enriched training sets, Neural Networks, 24, 814, 10.1016/j.neunet.2011.05.015

Wright, 2009, Robust face recognition via sparse representation, IEEE Trans. Pattern Anal. Mach. Intell., 31, 210, 10.1109/TPAMI.2008.79

Cotter, 2010, Sparse representation for accurate classification of corrupted and occluded facial expressions, 838

Liu, 2004, Gabor-based kernel pca with fractional power polynomial models for face recognition, IEEE Trans. Pattern Anal. Mach. Intell., 26, 572, 10.1109/TPAMI.2004.1273927

Liu, 2012, Facial expression recognition based on gabor features and sparse representation, 1402

Ahonen, 2006, Face description with local binary patterns: application to face recognition, IEEE Trans. Pattern Anal. Mach. Intell., 28, 2037, 10.1109/TPAMI.2006.244

M.R. Mohammadi, M. Jafarzadeh Zare, Robust facial expression recognition to noise using fuzzy local binary patterns, in: AISP 2012, 2012.

Ahonen, 2008, Recognition of blurred faces using local phase quantization, 1

Zhen, 2012, Facial expression recognition based on local phase quantization and sparse representation, 222

Do, 2012, Face recognition using co-occurrence histograms of oriented gradients, 1301

Gritti, 2008, Local features based facial expression recognition with face registration errors, 1

Li, 2012, Facial expression recognition based on rotation invariant local phase quantization and sparse representation, 1313

S. F. Cotter, Weighted voting of sparse representation classifiers for facial expression recognition, 2010.

Huang, 2010, A new method for facial expression recognition based on sparse representation plus lbp, vol. 4, 1750

Zafeiriou, 2010, Sparse representations for facial expressions recognition via ℓ1 optimization, 32

Mahoor, 2011, Facial action unit recognition with sparse representation, 336

Zhang, 2012, Robust facial expression recognition via compressive sensing, Sensors, 12, 3747, 10.3390/s120303747

Jeni, 2013, Continuous au intensity estimation using localized, sparse facial feature space, 1

Huang, 2007, Sparse representation for signal classification, Adv. Neural Inf. Process. Syst., 19, 609

Rubinstein, 2010, Dictionaries for sparse representation modeling, Proc. IEEE, 98, 1045, 10.1109/JPROC.2010.2040551

Aharon, 2006, K-svd: an algorithm for designing overcomplete dictionaries for sparse representation, IEEE Trans. Signal Process., 54, 4311, 10.1109/TSP.2006.881199

Engan, 2000, Multi-frame compression: theory and design, Signal Process., 80, 2121, 10.1016/S0165-1684(00)00072-4

J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman, Supervised dictionary learning, arXiv preprint. arXiv:0809.3083.

Yang, 2010, Metaface learning for sparse representation based face recognition, 1601

Ramirez, 2010, Classification and clustering via dictionary learning with structured incoherence and shared features, 3501

Zhang, 2010, Discriminative k-svd for dictionary learning in face recognition, 2691

Jiang, 2011, Learning a discriminative dictionary for sparse coding via label consistent k-svd, 1697

Yang, 2011, Fisher discrimination dictionary learning for sparse representation, 543

Calder, 2005, Understanding the recognition of facial identity and facial expression, Nat. Rev. Neurosci., 6, 641, 10.1038/nrn1724

W.V. Friesen, P. Ekman, Emfacs-7: emotional facial action coding system, Unpublished manuscript, University of California at San Francisco 2.

K. Shu, W. Donghui, A brief summary of dictionary learning based approach for classification, arXiv preprint. arXiv:1205.6391.

Donoho, 2006, For most large underdetermined systems of linear equations the minimal ℓ1-norm solution is also the sparsest solution, Commun. Pure Appl. Math., 59, 797, 10.1002/cpa.20132

Gorodnitsky, 1997, Sparse signal reconstruction from limited data using focuss: a re-weighted minimum norm algorithm, IEEE Trans. Signal Process., 45, 600, 10.1109/78.558475

Wohlberg, 2003, Noise sensitivity of sparse signal representations: reconstruction error bounds for the inverse problem, IEEE Trans. Signal Process., 51, 3053, 10.1109/TSP.2003.819006

Donoho, 2006, Stable recovery of sparse overcomplete representations in the presence of noise, IEEE Trans. Inf. Theory, 52, 6, 10.1109/TIT.2005.860430

Lucey, 2010, The extended Cohn-Kanade dataset (ck+): a complete dataset for action unit and emotion-specified expression, 94

Pantic, 2005, Web-based database for facial expression analysis

Savran, 2008, Bosphorus database for 3d face analysis, 47

Shan, 2009, Facial expression recognition based on local binary patterns: a comprehensive study, Image Vision Comput., 27, 803, 10.1016/j.imavis.2008.08.005

Amaldi, 1998, On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems, Theor. Comput. Sci., 209, 237, 10.1016/S0304-3975(97)00115-1

Chen, 1998, Atomic decomposition by basis pursuit, SIAM J. Sci. Comput., 20, 33, 10.1137/S1064827596304010

Mallat, 1993, Matching pursuits with time-frequency dictionaries, IEEE Trans. Signal Process., 41, 3397, 10.1109/78.258082

Mohimani, 2009, A fast approach for overcomplete sparse decomposition based on smoothed ℓ0 norm, IEEE Trans. Signal Process., 57, 289, 10.1109/TSP.2008.2007606

Babu, 2010, Linear systems, sparse solutions, and sudoku, IEEE Signal Process. Lett., 17, 40, 10.1109/LSP.2009.2032489

E. Candes, J. Romberg, ℓ1-Magic: recovery of sparse signals via convex programming. <www.acm.caltech.edu/l1magic/downloads/l1magic.pdf4>.

Pati, 1993, Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition, 40

Zhang, 2011, Sparse representation or collaborative representation: which helps face recognition?, 471

Mohammadi, 2014, Non-negative sparse decomposition based on constrained smoothed ℓ0 norm, Signal Process., 100, 42, 10.1016/j.sigpro.2014.01.010

Li, 2010, Facial expression recognition using facial-component-based bag of words and phog descriptors, Inf. Media Technol., 5, 1003

Khan, 2013, Framework for reliable, real-time facial expression recognition for low resolution images, Pattern Recognit. Lett., 34, 1159, 10.1016/j.patrec.2013.03.022

Sadeghi, 2013, Facial expression recognition using geometric normalization and appearance representation

Mohammadi, 2014, Simultaneous recognition of facial expression and identity via sparse representation

Mohammadi, 2013, Fuzzy local binary patterns: a comparison between min-max and dot-sum operators in the application of facial expression recognition

M. Valstar, M. Pantic, Induced disgust, happiness and surprise: an addition to the mmi facial expression database, in: Proc. Int’l Conf. Language Resources and Evaluation, W’shop on EMOTION, 2010, pp. 65–70.

Baltrusaitis, 2012, 3D constrained local model for rigid and non-rigid facial tracking, 2610

Miao, 2012, Cross-domain facial expression recognition using supervised kernel mean matching, vol. 2, 326

Gu, 2012, Facial expression recognition using radial encoding of local Gabor features and classifier synthesis, Pattern Recognit., 45, 80, 10.1016/j.patcog.2011.05.006