A survey on techniques to handle face recognition challenges: occlusion, single sample per subject and expression

[1]  LiLingjun,et al.  A survey of virtual sample generation technology for face recognition , 2018 .

[2]  Guoyong Qiu,et al.  A survey of virtual sample generation technology for face recognition , 2018, Artificial Intelligence Review.

[3]  Yao Zhao,et al.  A dimensionality reduction method based on structured sparse representation for face recognition , 2016, Artificial Intelligence Review.

[4]  Hugo Proença,et al.  Biometric recognition in surveillance scenarios: a survey , 2016, Artificial Intelligence Review.

[5]  Jian Yang,et al.  Adaptive noise dictionary construction via IRRPCA for face recognition , 2016, Pattern Recognit..

[6]  Xindong Wu,et al.  Corrupted and occluded face recognition via cooperative sparse representation , 2016, Pattern Recognit..

[7]  Jun Zhang,et al.  Improved sparse representation with low-rank representation for robust face recognition , 2016, Neurocomputing.

[8]  Jie Li,et al.  Joint dimensionality reduction for face recognition based on D-KSVD , 2016, 2016 International Conference on Machine Learning and Cybernetics (ICMLC).

[9]  Philippe De Wilde,et al.  Recognizing faces prone to occlusions and common variations using optimal face subgraphs , 2016, Appl. Math. Comput..

[10]  Mohamed Abdel-Mottaleb,et al.  Fully automatic face normalization and single sample face recognition in unconstrained environments , 2016, Expert Syst. Appl..

[11]  Jiexin Pu,et al.  Using the original and symmetrical face training samples to perform collaborative representation for face recognition , 2016 .

[12]  Jiwen Lu,et al.  Robust Point Set Matching for Partial Face Recognition , 2016, IEEE Transactions on Image Processing.

[13]  Mohamed Hammami,et al.  Face Recognition Through Different Facial Expressions , 2015, J. Signal Process. Syst..

[14]  Guoliang Yang,et al.  Sparse error via reweighted Low Rank Representation for face recognition with various illumination and occlusion , 2015 .

[15]  Zheng-ping Hu,et al.  Double layers sparse representation for occluded face recognition , 2015 .

[16]  Zheng-ping Hu,et al.  A modular weighted sparse representation based on Fisher discriminant and sparse residual for face recognition with occlusion , 2015, Inf. Process. Lett..

[17]  Changhui Hu,et al.  A new face recognition method based on image decomposition for single sample per person problem , 2015, Neurocomputing.

[18]  Ru-Xi Ding,et al.  Variational Feature Representation-based Classification for face recognition with single sample per person , 2015, J. Vis. Commun. Image Represent..

[19]  Shunfang Wang,et al.  Face recognition based on error detection under partial occlusion , 2015, 2015 12th International Conference on Service Systems and Service Management (ICSSSM).

[20]  Pethuru Raj,et al.  An approach to improvise recognition rate from occluded and pose variant faces , 2015, 2015 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC).

[21]  Yu-Chiang Frank Wang,et al.  Undersampled Face Recognition via Robust Auxiliary Dictionary Learning , 2015, IEEE Transactions on Image Processing.

[22]  Kien A. Hua,et al.  Face recognition from a single registered image for conference socializing , 2015, Expert Syst. Appl..

[23]  Rui Hu,et al.  Structured occlusion coding for robust face recognition , 2015, Neurocomputing.

[24]  Jun Cai,et al.  Single-Sample Face Recognition Based on Intra-Class Differences in a Variation Model , 2015, Sensors.

[25]  Jun Guo,et al.  Equidistant prototypes embedding for single sample based face recognition with generic learning and incremental learning , 2014, Pattern Recognit..

[26]  Tao Zhang,et al.  Producing virtual face images for single sample face recognition , 2014 .

[27]  Jamal El-Den,et al.  An MPCA/LDA Based Dimensionality Reduction Algorithm for Face Recognition , 2014 .

[28]  Min Wang,et al.  A novel virtual samples-based sparse representation method for face recognition , 2014 .

[29]  Sharif Muhammad,et al.  Face recognition invariant to partial occlusions , 2014 .

[30]  Shenghua Gao,et al.  Neither Global Nor Local: Regularized Patch-Based Representation for Single Sample Per Person Face Recognition , 2014, International Journal of Computer Vision.

[31]  Ibrahim Venkat,et al.  Recognition of occluded faces using an enhanced EBGM algorithm , 2014, 2014 International Conference on Computer and Information Sciences (ICCOINS).

[32]  Xinge You,et al.  Robust face recognition via occlusion dictionary learning , 2014, Pattern Recognit..

[33]  G. Priya,et al.  Occlusion invariant face recognition using mean based weight matrix and support vector machine , 2014, Sadhana.

[34]  M. V. Raghunadh,et al.  Illumination, Expression and Occlusion Invariant Pose-Adaptive Face Recognition System for Real-Time Applications , 2014, ArXiv.

[35]  Bin Fang,et al.  Extracting sparse error of robust PCA for face recognition in the presence of varying illumination and occlusion , 2014, Pattern Recognit..

[36]  Abdenour Hadid,et al.  Efficient Detection of Occlusion prior to Robust Face Recognition , 2014, TheScientificWorldJournal.

[37]  Weiping Chen,et al.  Face Recognition Using Ensemble String Matching , 2013, IEEE Transactions on Image Processing.

[38]  Bin Fang,et al.  Face recognition with contiguous occlusion using linear regression and level set method , 2013, Neurocomputing.

[39]  H. Ş. Bilge,et al.  Dimensionality reduction based on Lorentzian Manifold for face recognition , 2013, 2013 International Conference on Electronics, Computer and Computation (ICECCO).

[40]  Mohit Sharma,et al.  An efficient partial occluded face recognition system , 2013, Neurocomputing.

[41]  Biao Wang,et al.  Adaptive linear regression for single-sample face recognition , 2013, Neurocomputing.

[42]  Shiguang Shan,et al.  Adaptive discriminant learning for face recognition , 2013, Pattern Recognit..

[43]  Yan Liu,et al.  Joint discriminative dimensionality reduction and dictionary learning for face recognition , 2013, Pattern Recognit..

[44]  Simon C. K. Shiu,et al.  Gabor feature based robust representation and classification for face recognition with Gabor occlusion dictionary , 2013, Pattern Recognit..

[45]  Chang-Tsun Li,et al.  Fixation and Saccade Based Face Recognition from Single Image per Person with Various Occlusions and Expressions , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[46]  K. G. Subramanian,et al.  Recognizing occluded faces by exploiting psychophysically inspired similarity maps , 2013, Pattern Recognit. Lett..

[47]  D SathishKumar,et al.  REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION , 2013 .

[48]  Chang-Tsun Li,et al.  Face recognition with occlusion using Dynamic Image-to-Class Warping (DICW) , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[49]  Simon C. K. Shiu,et al.  Robust Kernel Representation With Statistical Local Features for Face Recognition , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[50]  J. Ming,et al.  Queen ' s University Belfast-Research Portal Robust Multimodal Person Identification With Limited Training Data , 2016 .

[51]  Jufu Feng,et al.  Reconstruction based face occlusion elimination for recognition , 2013, Neurocomputing.

[52]  R. Amutha,et al.  A novel approach to face recognition under various facial expressions, occlusion and tilt angles , 2012, 2012 International Conference on Emerging Trends in Science, Engineering and Technology (INCOSET).

[53]  Matti Pietikäinen,et al.  Towards a dynamic expression recognition system under facial occlusion , 2012, Pattern Recognit. Lett..

[54]  S Satonkar Suhas,et al.  Face Recognition Using Principal Component Analysis and Linear Discriminant Analysis on Holistic Approach in Facial Images Database , 2012 .

[55]  Gora Chand Nandi,et al.  Face recognition using facial symmetry , 2012, CCSEIT '12.

[56]  Lina Zhao,et al.  Face Recognition Feature Comparison Based SVD and FFT , 2012 .

[57]  Xia Han,et al.  Face Recognition in the Presence of Expressions , 2012 .

[58]  Guowei Yang,et al.  Class mean embedding for face recognition , 2011, Artificial Intelligence Review.

[59]  M. Mani Roja,et al.  Face recognition using discrete cosine transform for global and local features , 2011, 2011 INTERNATIONAL CONFERENCE ON RECENT ADVANCEMENTS IN ELECTRICAL, ELECTRONICS AND CONTROL ENGINEERING.

[60]  Gang Wang,et al.  Discriminative multi-manifold analysis for face recognition from a single training sample per person , 2011, 2011 International Conference on Computer Vision.

[61]  Qionghai Dai,et al.  Graph Laplace for Occluded Face Completion and Recognition , 2011, IEEE Transactions on Image Processing.

[62]  Jake K. Aggarwal,et al.  Is there a connection between face symmetry and face recognition? , 2011, CVPR 2011 WORKSHOPS.

[63]  Jian Yang,et al.  Robust sparse coding for face recognition , 2011, CVPR 2011.

[64]  Abdenour Hadid,et al.  Improving the recognition of faces occluded by facial accessories , 2011, Face and Gesture 2011.

[65]  Kaleem Siddiqi,et al.  Removal of Partial Occlusion from Single Images , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[66]  Weiping Chen,et al.  Recognizing Partially Occluded Faces from a Single Sample Per Class Using String-Based Matching , 2010, ECCV.

[67]  Kuo-Chin Fan,et al.  Robust face recognition under illumination and facial expression variations , 2010, 2010 International Conference on Machine Learning and Cybernetics.

[68]  Vinod Kumar,et al.  Pose invariant virtual classifiers from single training image using novel hybrid-eigenfaces , 2010, Neurocomputing.

[69]  Karim Faez,et al.  Recognizing faces using Adaptively Weighted Sub-Gabor Array from a single sample image per enrolled subject , 2010, Image Vis. Comput..

[70]  Longbing Cao,et al.  Expression-invariant facial identification , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[71]  Yongsheng Gao,et al.  Recognition of expression variant faces from one sample image per enrolled subject , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[72]  Zhi-Hua Zhou,et al.  Face Recognition Under Occlusions and Variant Expressions With Partial Similarity , 2009, IEEE Transactions on Information Forensics and Security.

[73]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[74]  Karim Faez,et al.  Face recognition using adaptively weighted patch PZM array from a single exemplar image per person , 2008, Pattern Recognit..

[75]  David Zhang,et al.  Face recognition using FLDA with single training image per person , 2008, Appl. Math. Comput..

[76]  Dattatray V. Jadhav,et al.  Radon and discrete cosine transforms based feature extraction and dimensionality reduction approach for face recognition , 2008, Signal Process..

[77]  Önsen Toygar,et al.  Recognizing faces under facial expression variations and partial occlusions , 2008 .

[78]  Eng Kiong Wong,et al.  Supervised Locally Linear Embedding in face recognition , 2008, 2008 International Symposium on Biometrics and Security Technologies.

[79]  Andrea F. Abate,et al.  2D and 3D face recognition: A survey , 2007, Pattern Recognit. Lett..

[80]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[81]  Martin D. Levine,et al.  Face recognition subject to variations in facial expression, illumination and pose using correlation filters , 2006, Comput. Vis. Image Underst..

[82]  Zhi-Hua Zhou,et al.  Face recognition from a single image per person: A survey , 2006, Pattern Recognit..

[83]  David Zhang,et al.  A novel dimensionality-reduction approach for face recognition , 2006, Neurocomputing.

[84]  Hao Zhang,et al.  Expression-Invariant Face Recognition with Expression Classification , 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

[85]  Katsuhiko Sakaue,et al.  Multi-view face recognition by nonlinear dimensionality reduction and generalized linear models , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[86]  Jongsun Kim,et al.  Effective representation using ICA for face recognition robust to local distortion and partial occlusion , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[87]  Xin Chen,et al.  Fully automated facial symmetry axis detection in frontal color images , 2005, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05).

[88]  Zhi-Hua Zhou,et al.  Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft k-NN ensemble , 2005, IEEE Transactions on Neural Networks.

[89]  Yutao Qi,et al.  Robust visual similarity retrieval in single model face databases , 2005, Pattern Recognit..

[90]  Jieping Ye,et al.  A two-stage linear discriminant analysis via QR-decomposition , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[91]  Daoqiang Zhang,et al.  A new face recognition method based on SVD perturbation for single example image per person , 2005, Appl. Math. Comput..

[92]  J. Zhang,et al.  Global exponential stability of a class of neural networks with variable delays , 2005 .

[93]  Rama Chellappa,et al.  A method for converting a smiling face to a neutral face with applications to face recognition , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[94]  Xiaofei He,et al.  Locality Preserving Projections , 2003, NIPS.

[95]  Jian-Huang Lai,et al.  Component-based LDA method for face recognition with one training sample , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).

[96]  Aleix M. Martínez,et al.  Recognizing expression variant faces from a single sample image per class , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[97]  Marian Stewart Bartlett,et al.  Face recognition by independent component analysis , 2002, IEEE Trans. Neural Networks.

[98]  K. Kim,et al.  Face recognition using kernel principal component analysis , 2002, IEEE Signal Process. Lett..

[99]  Yongsheng Gao,et al.  Face Recognition Using Line Edge Map , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[100]  Aleix M. Martínez,et al.  Recognizing Imprecisely Localized, Partially Occluded, and Expression Variant Faces from a Single Sample per Class , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[101]  N. Jamil,et al.  Face recognition using neural networks , 2001, Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century..

[102]  Ming-Hsuan Yang,et al.  Face Recognition Using Kernel Methods , 2001, NIPS.

[103]  S T Roweis,et al.  Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.

[104]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[105]  Guodong Guo,et al.  Face recognition by support vector machines , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[106]  Shaogang Gong,et al.  Support vector regression and classification based multi-view face detection and recognition , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[107]  Bernhard Schölkopf,et al.  Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.

[108]  Thomas Vetter,et al.  Synthesis of Novel Views from a Single Face Image , 1998, International Journal of Computer Vision.

[109]  Rama Chellappa,et al.  Discriminant Analysis for Recognition of Human Face Images (Invited Paper) , 1997, AVBPA.

[110]  H. Bülthoff,et al.  Bilateral symmetry of human faces helps to generalize to novel views , 1996 .

[111]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[112]  K. N. Balasubramanya Murthy,et al.  Two Dimensionality Reduction Techniques for SURF Based Face Recognition , 2016 .

[113]  Sandesh V Khamele,et al.  An Approach for Restoring Occluded Images for Face-Recognition , 2015 .

[114]  P. Raj.  An Efficient Method to Recognize Human Faces From Video Sequences with Occlusion , 2015 .

[115]  Jiang-She Zhang,et al.  Singular Value Decomposition Projection for solving the small sample size problem in face recognition , 2015, J. Vis. Commun. Image Represent..

[116]  Julio Jacobo-Berlles,et al.  Face recognition on partially occluded images using compressed sensing , 2014, Pattern Recognit. Lett..

[117]  K Vimala,et al.  Optical Flow Based Face Recognition under Expression Variations , 2014 .

[118]  C. JayaMohan,et al.  Face Recognition under Expressions and Lighting Variations using Artificial Intelligence and Image Synthesizing , 2013 .

[119]  S. Chitra,et al.  A SURVEY OF FACE RECOGNITION ON FEATURE EXTRACTION PROCESS OF DIMENSIONALITY REDUCTION TECHNIQUES , 2012 .

[120]  Resmi R. Nair,et al.  Face Recognition under Expressions and Lighting Variations using Masking and Synthesizing , 2012 .

[121]  Amir Akramin Shafie,et al.  Face recognition from single sample per person by learning of generic discriminant vectors , 2012 .

[122]  Vin de Silva,et al.  Reduction A Global Geometric Framework for Nonlinear Dimensionality , 2011 .

[123]  Shang-Hong Lai,et al.  An Optical Flow-Based Approach to Robust Face Recognition Under Expression Variations , 2010, IEEE Transactions on Image Processing.

[124]  Sang Uk Lee,et al.  Occlusion Invariant Face Recognition Using Two-Dimensional PCA , 2006, VISIGRAPP.

[125]  Daoqiang Zhang,et al.  An Efficient Pseudoinverse Linear Discriminant Analysis method for Face Recognition , 2006 .

[126]  Hakan Cevikalp,et al.  Discriminative common vectors for face recognition , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[127]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.