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A Survey on Classical and Modern Face Recognition Techniques

M. ShalimaSulthana, C. NagaRaju
2021 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
In addition to traditional face recognition approaches, the most recent research topics such as sparse models, deep learning, and fuzzy set theory are examined in depth.  ...  As a result of our research; we've outlined some of the most important applications, difficulties, and trends in scientific and social domains.  ...  After that An image is compared to images in the database using tolerance rough set-based similarity.  ... 
doi:10.32628/cseit21762 fatcat:ihjeygme6fem3bkas2nalzkywe

A Novel Technique to Enhance Performance of Multibiometric Framework using Bin based Classifier Based on Multi-algorithm Score Level Fusion

An optimization technique, PSO is utilized to minimize the unwanted information after combination of the feature sets of the iris and face using different feature extraction algorithms like PCA, LDA and  ...  In this work Bin based classifier is used as the combination rule which integrate the matching scores from two distinct modalities namely iris and face.  ...  Two face database (ORL and Yale) and CASIA iris database are used to validate the proposed algorithm.  ... 
doi:10.35940/ijitee.c8773.019320 fatcat:iqonuja43jhcvd36punl54zirq

Face Recognition on a Smart Image Sensor Using Local Gradients

Wladimir Valenzuela, Javier E. Soto, Payman Zarkesh-Ha, Miguel Figueroa
2021 Sensors  
Our face recognition method, which is based on Ahonen's algorithm, operates in three stages: (1) it extracts local image features using RLBP, (2) it computes a feature vector using RLBP histograms, (3)  ...  The smart pixel achieves a fill factor of 34% on the 0.35 μm process and 76% on a 0.18 μm process with 32 μm × 32 μm pixels. The pixel array operates at up to 556 frames per second.  ...  Accuracy of our RLBP+LDA and LBP+LDA methods compared to other face classification algorithms discussed in [83] , using the Yale face database B [82] .  ... 
doi:10.3390/s21092901 pmid:33919130 fatcat:msoavyvkmve7nh5r75mbqdzcky

Equidistant prototypes embedding for single sample based face recognition with generic learning and incremental learning

Weihong Deng, Jiani Hu, Xiuzhuang Zhou, Jun Guo
2014 Pattern Recognition  
Using this novel method, learning based on only a handful of generic classes can largely improve the face recognition performance, even when the generic data are collected from a different database and  ...  We develop a parameter-free face recognition algorithm which is insensitive to large variations in lighting, expression, occlusion, and age using a single gallery sample per subject.  ...  SRC (sparse representation classifier) [34] is an up-to-date classification method using ℓ 1 minimization, and achieves impressive performance on Extended Yale B database.  ... 
doi:10.1016/j.patcog.2014.06.020 fatcat:jzlv2svvbvfbpbfumjkcbsql6u

Face recognition

W. Zhao, R. Chellappa, P. J. Phillips, A. Rosenfeld
2003 ACM Computing Surveys  
For example, recognition of face images acquired in an outdoor environment with changes in illumination and/or pose remains a largely unsolved problem.  ...  There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the studies  ...  Using the Yale and Weizmann databases (Table V) , significant performance improvements were reported when the prototype images were used in a subspace LDA system in place of the original input images  ... 
doi:10.1145/954339.954342 fatcat:3bx4i7gsjvbrbguiv4u2jekytu

Automated border control e-gates and facial recognition systems

Jose Sanchez del Rio, Daniela Moctezuma, Cristina Conde, Isaac Martin de Diego, Enrique Cabello
2016 Computers & security  
To conclude, improvements that could be implemented in the near future in ABC face recognition systems are described.  ...  In addition, the results of an experimental evaluation of a face recognition system when halogen, white LEDs, near infra-red, or fluorescence illumination was used, which was conducted in order to determine  ...  Scale invariant feature transform (SIFT) for features extraction and an SVM for classification was used with the ORL and Yale face databases.  ... 
doi:10.1016/j.cose.2016.07.001 fatcat:66gvociowffihdov4ivzihokmm

Multi-classifier ensemble based on dynamic weights

Fuji Ren, Yanqiu Li, Min Hu
2017 Multimedia tools and applications  
Compared with other methods, the contribution of different classifiers to fusion decision in acquiring weights is fully evaluated in consideration of the capability of the classifier to not only identify  ...  In this study, a novel multi-classifier ensemble method based on dynamic weights is proposed to reduce the interference of unreliable decision information and improve the accuracy of fusion decision.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s11042-017-5480-5 fatcat:45zj5ee6tvdmjghittl3xktck4

Face Detection and Recognition Method Based on Improved Convolutional Neural Network

Zhengqiu Lu, Chunliang Zhou, Xuyang Xuyang, Weipeng Zhang
2021 North atlantic university union: International Journal of Circuits, Systems and Signal Processing  
In order to solve the problems of information loss and equal treatment of each element in the input feature graph in the traditional pooling method of convolutional neural network, a face recognition algorithm  ...  The experimental results show that this method has good face recognition accuracy in common face databases.  ...  It searches and matches the extracted face image feature data with the feature template stored in the database, and then compares the face feature to be recognized with the face feature template by setting  ... 
doi:10.46300/9106.2021.15.85 fatcat:rfqpj6lpkrcxpbo5opptn4zc6q

Pixel-Level Decisions based Robust Face Image Recognition [chapter]

Alex Pappachen
2010 Face Recognition  
In the comparison of images this translates into pixel to pixel local similarity calculation followed by an application of a (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) (m) (o) (p) (q) (r) (s) (t)  ...  Feature localization in humans is handled by feedback mechanisms linked to human eye and brain.  ...  This book aims to bring together selected recent advances, applications and original results in the area of biometric face recognition.  ... 
doi:10.5772/8950 fatcat:jyrsykckg5f47ekowc2c32hubi

Predictive Modeling of Hospital Readmission: Challenges and Solutions [article]

Shuwen Wang, Xingquan Zhu
2021 arXiv   pre-print
modeling hospital readmission; what are typical features/models used for readmission prediction; how to achieve meaningful and transparent predictions for decision making; and what are possible conflicts  ...  In this paper, we systematically review computational models for hospital readmission prediction, and propose a taxonomy of challenges featuring four main categories: (1) data variety and complexity; (  ...  Given a dataset D = [X 1 , X 2 , · · · , X n ] ∈ R n×m with n instances and m original features, and each instance X i ∈ R m is denoted by an m dimensional features, the classical autoencoder objective  ... 
arXiv:2106.08488v1 fatcat:g5hk5feahrgjfkixu4ep2qdlbq

Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns

2018 IEEE Control Systems  
In particular, drastic reductions in the required number of sensors and improved reconstruction are observed in examples ranging from facial images to fluid vorticity fields.  ...  Sparse sensing in a tailored basis is contrasted with compressed sensing, a universal signal recovery method in which an unknown signal is reconstructed via a sparse representation in a universal basis  ...  The extended Yale B face database [78, 79] is a canonical dataset used for facial recognition, and it is an ideal test bed for recovering low-rank structure from high-dimensional pixel space.  ... 
doi:10.1109/mcs.2018.2810460 fatcat:iy7j5eqtifd55cvg4r4baxvgmq

Alzheimer's Disease Diagnosis Based on Cognitive Methods in Virtual Environments and Emotions Analysis [article]

Juan Manuel Fernández Montenegro
2018 arXiv   pre-print
EEG features are based on quaternions in order to keep the correlation information between sensors, whereas, for facial expression recognition, a preprocessing method for motion magnification and descriptors  ...  Novel AD's screening tests based on virtual environments using new immersive technologies combined with advanced Human Computer Interaction (HCI) systems are introduced.  ...  EEG techniques need to be improved in order to obtain more reliable feedback. Currently deep learning techniques are being effectively used in many areas.  ... 
arXiv:1810.10941v1 fatcat:lrqvy6gqkvhszkxffxbq5iyut4

Face Recognition by Computers and Humans

Rama Chellappa, Pawan Sinha, P. Jonathon Phillips
2010 Computer  
has also proven useful in applications such as human-computer interaction, virtual reality, database retrieval, multimedia, and computer entertainment  ...  then compares them with the enrolled representations of subjects in the database.  ... 
doi:10.1109/mc.2010.37 fatcat:lpttfczwk5g2boj2f7chtx6r6i

A Chronological Review on Face Detection Algorithms Used in Modern Surveillance Systems

Sapna Rathore
2021 International Journal for Research in Applied Science and Engineering Technology  
Index Terms: Face detection, challenges, noise, features.  ...  In this article we have reviewed various prominent approaches for facial detection ranging from classical edge based detection to neural network based model.  ...  This procedure strives to enhance denoising accuracy with the help of an optimised excess weight kernel of an NLM filter and improved local community pre-classification algorithm criteria.  ... 
doi:10.22214/ijraset.2021.38900 fatcat:toprie6qefe3zovjc6agakgifa

Facial Expression Recognition: A Review of Trends and Techniques

Olufisayo Ekundayo, Serestina Viriri
2021 IEEE Access  
Facial Expression Recognition (FER) is presently the aspect of cognitive and affective computing with the most attention and popularity, aided by its vast application areas.  ...  We proceed to provide a comprehensive FER review in three different machine learning problem definitions: Single Label Learning (SLL)-which presents FER as a multiclass problem, Multilabel Learning (MLL  ...  [141] used Significant Non-Uniform LBP combined with uLBP features to improve the FER recognition rate.  ... 
doi:10.1109/access.2021.3113464 fatcat:hapy6t6ohneupiwh7meakzk3ma
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