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Structured occlusion coding for robust face recognition
2016
Neurocomputing
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Recently, several occlusion dictionary based approaches [13] [14] [15] [16] for robust face recognition have been attached more and more importance. ...
Occlusion in face recognition is a common yet challenging problem. ...
Robust face recognition with unlabeled occluded images As shown in 4.3, the proposed algorithm is effective in handling real occlusion with a well-trained occlusion dictionary. ...
doi:10.1016/j.neucom.2015.05.132
fatcat:iwti42ehonemdp5wepqaf6wwsq
Structured Occlusion Coding for Robust Face Recognition
[article]
2015
arXiv
pre-print
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Occlusion in face recognition is a common yet challenging problem. ...
In order to construct a well-performing occlusion dictionary, we propose an occlusion mask estimating technique via locality constrained dictionary (LCD), showing striking improvement in occlusion sample ...
Recently, several occlusion dictionary based approaches [13] [14] [15] [16] for robust face recognition have been attached more and more importance. ...
arXiv:1502.00478v2
fatcat:765cpr2dhveezbfmag4aiak4oa
Fast and robust face recognition via coding residual map learning based adaptive masking
2014
Pattern Recognition
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Robust face recognition (FR) is an active topic in computer vision and biometrics, while face occlusion is one of the most challenging problems for robust FR. ...
A dictionary is learned to code the training samples, and the distribution of coding residuals is computed. Consequently, a residual map is learned to detect the occlusions by adaptive thresholding. ...
However, CRC_RLS has no special settings to deal with occlusion and it is less robust to occluded faces.
3 Coding residual map learning
Dictionary learning In representation based FR, the recognition ...
doi:10.1016/j.patcog.2013.08.003
fatcat:tn4oiurvnfh2xmqdr7n4fpg3tu
Undersampled Face Recognition via Robust Auxiliary Dictionary Learning
2015
IEEE Transactions on Image Processing
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Index Terms-Dictionary learning, sparse representation, face recognition. 1057-7149 ...
This is achieved by the learning of a robust auxiliary dictionary from the subjects not of interest. ...
Undersampled Face Recognition via Robust Auxiliary Dictionary Learning
I. ...
doi:10.1109/tip.2015.2409738
pmid:25769163
fatcat:cxussrnfkbeyxhhfpjydqn2rsa
Smart computing for large scale visual data sensing and processing
2016
Neurocomputing
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The paper Structured Occlusion Coding for Robust Face Recognition by Wen et al. aims to improve the robustness of sparse representation based classification (SRC) against occlusion. ...
better robustness to real occlusion on the CAS-PEAL and AR face datasets. ...
doi:10.1016/j.neucom.2015.10.108
fatcat:sddvsdidozdlthvrlqannhddx4
A Survey on Face Recognition Techniques for Undersampled Data
2017
International Journal of Science and Research (IJSR)
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In this Survey paper, different types of Undersampled Face Recognition methods are analyzed. ...
Due to an increase of the Globalization and digitization around the world, the Face Recognition technology gains a lot of importance for identification purpose. ...
Face Recognition via Robust Auxiliary Dictionary Learning In ESRC [12] the given input image is supposed to know the type of occlusion of image y and present in the dictionary A which is not possible ...
doi:10.21275/art20164288
fatcat:rasfmpezdvgwtduanfsxg56jeq
Undersampled face recognition with one-pass dictionary learning
2015
2015 IEEE International Conference on Multimedia and Expo (ICME)
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Moreover, our computation time is remarkably less than that of recent dictionary learning based face recognition methods. ...
Undersampled face recognition deals with the problem in which, for each subject to be recognized, only one or few images are available in the gallery (training) set. ...
FACE RECOGNITION VIA ONE-PASS DICTIONARY LEARNING
Extending ESRC for Robust Face Recognition We now present our proposed algorithm for undersampled (including single sample) face recognition. ...
doi:10.1109/icme.2015.7177451
dblp:conf/icmcs/WeiW15
fatcat:2kzxt7d775d4dpcbvjz4szc5nq
HSR: L 1/2-regularized sparse representation for fast face recognition using hierarchical feature selection
2015
Neural computing & applications (Print)
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2014 pre-print arXiv:1409.6448v1 fatcat:5z3jbu3xsjedpfvvpvchoxzsfu
Besides, in the presence of occluded face image, the scale of Gabor-feature based global dictionary can be compressed accordingly because redundancies exist in Gabor-feature based occlusion dictionary. ...
In this paper, we propose a novel method for fast face recognition called L1/2 Regularized Sparse Representation using Hierarchical Feature Selection (HSR). ...
Moreover, in the presence of occluded faces, we can obtain a compact occlusion dictionary via sparse coding because of redundancies in Gabor-feature based occlusion dictionary, thus the scale of global ...
doi:10.1007/s00521-015-1907-y
fatcat:qlbhvzjnpjgw3k477gvzoiib2e
A Review of Face Recognition Techniques
2016
Journal of excellence in Computer Science and Engineering
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Streams including content retrieval, network security and video compression get profited by face recognition technology. ...
As the requirement of high level of security arises, face recognition technology is bound to bend, to cope with the upcoming needs. ...
Extended Sparse Representation-Based Classification (ESRC)
Robust auxiliary dictionary learning [24] addresses the problem of undersampled face recognition by learning the Robust Auxiliary Dictionary ...
doi:10.18831/djcse.in/2016021002
fatcat:babgzcmqw5c5datil4yapqxoge
With one look
2013
Proceedings of the 21st ACM international conference on Multimedia - MM '13
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In this paper, we address the problem of robust face recognition using single sample per person. ...
., images of subjects not of interest) for learning an exemplar-based dictionary. ...
Acknowledgement This work is supported in part by National Science Council of Taiwan via NSC100-2221-E-001-018-MY2. ...
doi:10.1145/2502081.2502158
dblp:conf/mm/HuangW13
fatcat:4m5igpwyqbbdpbtpmmexqhnicu
Gabor feature based robust representation and classification for face recognition with Gabor occlusion dictionary
2013
Pattern Recognition
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face recognition (FR). ...
Particularly, by introducing an identity occlusion dictionary to code the occluded portions of face images, SRC could lead to robust FR results against face occlusion. ...
Abbreviation
Meaning
FR
Face Recognition
GOD
Gabor Occlusion Dictionary
GRR
Gabor-feature based Robust Representation
GRRC
Gabor-feature based Robust Representation based Classification
GRRC_L ...
doi:10.1016/j.patcog.2012.06.022
fatcat:qav35knvendbtmm5gqwpqkgkie
Learning Kernel-Based Robust Disturbance Dictionary for Face Recognition
2019
Applied Sciences
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In this paper, a kernel-based robust disturbance dictionary (KRDD) is proposed for face recognition that solves the problem in modern dictionary learning in which significant components of signal representation ...
In the experimental results, KRDD performance displays great advantages in recognition rate and computation time compared with many of the most advanced dictionary learning methods for face recognition ...
To improve the performance of dictionary learning in face recognition, a new kernel-based robust disturbance dictionary (KRDD) model for face recognition is proposed by combining KDA, SRC and KPCA. ...
doi:10.3390/app9061189
fatcat:htrkssu7yvdlzikaniy4mukata
Sparse Variation Dictionary Learning for Face Recognition with a Single Training Sample per Person
2013
2013 IEEE International Conference on Computer Vision
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Face recognition (FR) with a single training sample per person (STSPP) is a very challenging problem due to the lack of information to predict the variations in the query sample. ...
, occlusion, pose, etc., can be better handled. ...
Conclusion We proposed a sparse variation dictionary learning (SVDL) method, which learns a sparse variation dictionary from a generic training set to improve face recognition performance with a single ...
doi:10.1109/iccv.2013.91
dblp:conf/iccv/YangGZ13
fatcat:7tifvesqbrfena7a3yh7ml24da
Face Recognition Based on Discriminative Dictionary with Multilevel Feature Fusion
[chapter]
2014
Lecture Notes in Computer Science
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In order to alleviate the influence of illumination, pose, expression and occlusion variations in face recognition, in this paper, an effective face recognition method based on discriminative sparse representation ...
To solve the problem of these variations, we extract discriminative features which represent for each of the training images, and propose a novel dictionary by learning discriminative features. ...
The dictionary constructed via NSCT can optimize the discriminative features and is more robust. ...
doi:10.1007/978-3-319-11656-3_23
fatcat:a4t2sbdi25ggnlth4laxobb534
Low-rank representations with incoherent dictionary for face recognition
[article]
2019
arXiv
pre-print
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To this end, a correlation penalty term is introduced into the formulation of our proposed method to learn an incoherent dictionary. ...
In this paper, we propose a novel semi-supervised method based on the theory of the low-rank matrix recovery for face recognition, which can simultaneously learn discriminative low-rank and sparse representations ...
[18] proposed a robust low-rank recovery algorithm (RLRR) with a distance-measure structure for face recognition. ...
arXiv:1912.04478v1
fatcat:qdpqawnpq5d6vjgw7usqwfrvaq
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