FACE RECOGNITION-TECHNOLOGY IEEE PAPERS AND PROJECTS-2020



Face Recognition Technology is the future generation recognition system that provides an incredibly versatile human verification process.



Caption-supervised face recognition : Training a state-of-the-art face model without manual annotation
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The advances over the past several years have pushed the performance of face recognition to an amazing level. This great success, to a large extent, is built on top of millions of annotated samples. However, as we endeavor to take the performance to the next level, the

A novel non-linear modifier for adaptive illumination normalization for robust face recognition
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In this paper, a novel approach is presented for adaptive illumination normalization for face recognition under varying illuminations due to change in angle of light projection. Illumination normalization is performed over some of the low frequency discrete Cosine

FAN- Face : a Simple Orthogonal Improvement to Deep Face Recognition .
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It is known that facial landmarks provide pose, expression and shape information. In addition, when matching, for example, a profile and/or expressive face to a frontal one, knowledge of these landmarks is useful for establishing correspondence which can help Face recognition is the process of identifying people through facial images. It has become vital for security and surveillance applications and required everywhere including institutions, organizations, offices, and social places. There are a number of challenges

Face Recognition Vendor Test (FRVT) Part 4: MORPH Performance of Automated Face Morph Detection
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Background Face morphing and the ability to detect it is an area of high interest to photo- credential issuance agencies, companies, and organizations employing face recognition for identity verification. Face morphing is an image manipulation technique where two or moreTill today attendance marking is manual event for many educational bodies. It is a mandatory, common and important activity in day to day life of a faculty member. Manual attendances maintaining is bit difficult process, time consuming effort while doing analysis or

Improving Face Recognition from Hard Samples via Distribution Distillation Loss
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Large facial variations are the main challenge in face recognition . To this end, previous variation-specific methods make full use of task-related prior to design special network losses, which are typically not general among different tasks and scenarios. In contrast, the This paper proposes a novel Eigen face recognition that is aided by fusion of visible and thermal face images to improve the face recognition accuracy. We adopt three different fusion schemes where in the face information is fused by the optimal weights obtained by In the field of face recognition a key issue is whether there are a sufficient number of face training samples with valid information. Due to the complexity of human face images, face recognition is easy to be affected by the external environment such as light intensity, gesture In recent years, convolutional neural networks have proven to be a highly efficient approach for face recognition . In this paper, we develop such a framework to learn a robust face verification in an unconstrained environment using aggressive data augmentation. Our In this paper, a novel 3D face reconstruction technique is proposed along with a sequential deep learning-based framework for face recognition . It uses the voxels generated from the voxelization process. It uses the reflection principle for generating the reconstructed point in Abstract Description and classification of face images is a significant task of computer vision, machine learning and pattern recognition communities. In the past, researchers have made tremendous efforts in this task. Previous researchers always seek high-resolution face Abstract Modern Face Recognition (FR) systems have to cope with high intra-class variability. Face is a 3D object with wide variability in appearances from each pose. This, along with other causes like luminance variation, becomes one of the main reasons for the

Illumination-robust face recognition based on deep convolutional neural networks architectures
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In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology. In this research paper, we present a Face Recognition (FR) system divided into three steps: The Viola-Jones face detection algorithm, facial image

Akin-based Orthogonal Space (AOS): a subspace learning method for face recognition
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A projection learning space is an approach to mapping a high-dimensional vector space to a lower dimensional vector space. In this paper, we proposed an algorithm, namely, AOS: Akin based Orthogonal Space. The algorithm is driven with two major targets-(i) to choose most

Face Recognition Based on Relative Gradient Magnitude Strength
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Face recognition (FR) is a remarkable and attractive research field in pattern recognition and computer vision. FR is still a challenging problem due to the following obstacles: illumination, posture, wearing of glasses/scarves, or facial expression. To overcome these

Face Recognition Based on MTCNN and Convolutional Neural Network
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MTCNN is a face detection method based on deep learning, which is more robust to light, angle and facial expression changes in natural environment, and has better face detection effect. At the same time, the memory consumption is small, and real-time face detection can Age-invariant face recognition is one of the most crucial computer vision problems, eg, in passport verification, surveillance systems, and missing individuals identification. The extraction of robust face features is a challenge since the facial characteristics change over

A Novel Approach of Face Recognition Using Optimized Adaptive Illumination Normalization and KELM
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Light variations from different directions on the face images cause severe performance degradation in face recognition system. These variations should be nullified or suppressed so that the recognition performance can be improved. Here, the objective is to develop a Face recognition (FR) based on image set is an important topic in computer vision. There are numerous approaches that apply pose estimation method for single image face recognition but few embed pose estimation method into image set-based face recognition

A novel hybrid genetic wolf optimization for newborn baby face recognition
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Biometric secured system to avoid the Missing, swapping and illegal adoption of newborn baby is a global challenge and research done to solve this issue is minimal and least reported in the literature. Biometric face recognition is a novel approach to non-invasive

Face Recognition based Android Application to Take Students Attendance
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The purpose of our project is to save time during class. Typically, each class has a duration of 50 to 60 minutes. During this time, getting attendance, given lectures and there are many different tasks. And our system is to save time during Attendance. Our system will be done

Multi-Objective Particle Swarm Optimization-based Feature Selection for Face Recognition
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The curse of dimensionality is a well-known problem in biometric applications (eg, biometric passports). The downside of this problem is that both the accuracy and speed of the biometric authentication process are reduced. This paper sets forth a feature selection (FS)

Face Recognition
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Face Recognition has become a advanced concept in Machine Learning, Deep Learning and goes for to Artificial Intelligence. Face recognition has many applications in this world like from viewing someones face in group photo in social media, and the concept of deep

SURVEY ON DIFFERENT APPROCHES IN FACE RECOGNITION
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Humans can detect and identify faces in a scene with no effort. However, building a computerized system that achieves this task is very problematic. There are a few sub issues related to face recognition : recognition of an example as a face ID of the face investigation

3D DEFORMATION SIGNATURE FOR DYNAMIC FACE RECOGNITION
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This work proposes a novel 3D Deformation Signature (3DS) to represent a 3D deformation signal for 3D Dynamic Face Recognition . 3DS is computed given a non-linear 6D-space representation which guarantees physically plausible 3D deformations. A unique

Texture based FACE recognition using GLCM and LBP schemes
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K Kumar, AA Wagan Indian Journal sciresol.s3.us-east-2.amazonaws Objectives: Automatic face recognition has been an important area of biometric authentication and verification system in various applications including crime detection, access control, video surveillance, tracking service and other related area

Improving Face Recognition Methods based on POEM Features.
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POEM descriptors has been successfully used for face recognition . The usual way how the descriptor is utilized consists in constructing POEM features in the rectangular non- overlapping regions covering the whole image. The features created in the regions are then

Low Resolution Face Recognition Using Generative Adversarial Network (Gan)
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Although face recognition system has achieved a very good performance in the past years, but Low Resolution Face Recognition (LRFR) is still challenging because low resolution image would decrease the accuracy. This research aimed to solved and get the best SR

Chapter-7 Face Recognition using LBP-Based Adaptive Directional Wavelet Transform
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Face recognition is a key issue in biometric identification which now requires extracting more robust local descriptive features to efficiently deal with various facial variations such as pose, expressions and illumination variations. Various multi-resolution analysis (MRA)

Face Recognition Based Attendance System
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To detect real time human face are used and a simple fast Principal Component Analysis has used to recognize the faces detected with a high accuracy rate. The matched face is used to mark attendance of the students. Our system maintains the attendance records of

Illumination Compensation of Facial Image Using Combination Algorithm for Face Recognition
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So far, biometric identification in general and facial recognition in particular are still being researched and developed for applying in several areas such as security, etc. In this paper, the authors study on some facial image recognition methods that have been researched and

A Comparative Study of Face Recognition Classification Algorithms
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Due to the different classification effects and accuracy of different classification algorithms in machine learning, it is inconvenient for scientific researchers to choose which classification algorithm to use. This paper uses the face data published by Cambridge University as an

FACE RECOGNITION BASED SECURITY SYSTEM USING DEEP LEARNING
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Now days, Security plays an important role in day-to-day life. The use of the internet in human life has become the day to day activity and with the internet the use of automation devices has increased. All transaction needs to secure authentication to complete. Hence

A survey of face recognition technology
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This paper provides a brief insight of some well-known and very important algorithm used for face detection. Face detection technology is used by the computer system/for detecting faces in a digital image that is given. Automatic face detection is a very complex issue in image ABSTRACT Closed-Circuit Television (CCTV) is a device generally used for security, and it is widely installed and utilized in shopping malls, grocery stores, offices, industries, housing, factories, transportation units, and other public places. CCTV can be further optimized to Automatic face recognition technologies have made many improvements within the changing world. We have find a real world solution for automatic student attendance system in a classroom using Real-Time Face Recognition . In order to reduce the humanIn the previous few years, the procedures of face recognition have been researched thoroughly. Well-versed reviews, for various human face recognition methodologies, are provided in this paper. Initially, we proffer a summary of face recognition with its application Large facial variations are the main challenge in face recognition . To this end, previous variation-specific methods make full use of task-related prior to design special network losses, which are typically not general among different tasks and scenarios. In contrast, the

FACE RECOGNITION SYSTEM FOR VISUALLY IMPAIRED PEOPLE
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In our proposed method, a real time System Recognition Face (FRS) introduced for low vision people and aiding the blind. The work process includes face detection and face recognition to identify the person who is standing in front of them. First, the captured image is

Face recognition based on curvelets, invariant moments features and SVM
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Recent studies highlighted on face recognition methods. In this paper, a new algorithm is proposed for face recognition by combining Fast Discrete Curvelet Transform (FDCvT) and Invariant Moments with Support vector machine (SVM), which improves rate of face

Application of Novel Gabor-DCNN into RGB-D Face Recognition .
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In this paper, we propose a novel approach, named Gabor-DCNN, applied for face recognition technology of two modalities RGB-D images, which can extract the features through Gabor transform of images and deep convolutional neural network. Gabor transformScience has taken a great leap in recent time. Artificial intelligence is one of the field which has shown a rapid growth. These technologies have greatly reduced the effort which we used to put in our day to day work earlier. Face Recognition is one of such technology. TheThe technology of face recognition is attractive and full of technology research challenges; It is used for recognizing people by using digital images. Although face recognition has an important role in several areas such as security, face recognition technology still encounters

Efficient Masked Face Recognition Method during the COVID-19 Pandemic
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The COVID-19 is an unparalleled crisis leading to huge number of casualties and security problems. In order to reduce the spread of coronavirus, people often wear masks to protect themselves. This makes the face recognition a very di cult task since certain parts of the face

Face Recognition with Age, Gender and Emotion Estimations
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In this paper, we propose an application that can be used to help retail industries adjust purchase lists and operation modes to increase sales and improve service quality. The convolutional neural network and residual network structures are used to estimate the age

Attendance Management System Using Face Recognition
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The purpose of this project is to build attendance management system based on face recognition Face recognition is an important application of Image processing owing to its use in many fields. Identification of candidate in an organization for the purpose of

Neuro-fuzzy inference system based face recognition using feature extraction
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Human face recognition (HFR) is the method of recognizing people in images or videos. There are different HFR methods such as feature-based, eigen-faces, hidden markov model and neural network (NN) based methods. Feature extraction or preprocessing used in first

Smart Attendance System Using Face Recognition
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Making Attendance as smarter using recent technology and recognition in deep learning algorithms to build a system that will detect and recognize frontal faces of students in a classroom. A face is the front part of a persons head from the forehead to the chin, or the Human face conveys more information about identification, expression, and emotions of a person. In todays world every individual in the society wants to be more secure from unauthorized authentication. In order to provide more security, Facial Recognition has The goal of the study is to increase the computation efficiency of the face recognition that uses feature vectors to describe facial images on photos and videos. These high- dimensional feature vectors are nowadays produced by convolutional neural networks. The

A Comparative Efficiency of Face Recognition Using Face Features Analysis and Artificial Neural Network
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This research proposed a human- face recognition system by using Geometrical Face Feature Analysis and Artificial Neural Network (GFFA/ANN). In this study, we presented and compared the effectiveness of human- face recognition by using two different face feature

Face Recognition Using CBIR and Genetic Algorithm
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Face recognition is used worldwide for security purposes. The data used for facial recognition are frontal face images and retrieval of these images from the database is done using Content Based Image Retrieval or CBIR. Facial image recognition is done by

Jointly De-biasing Face Recognition and Demographic Attribute Estimation (Supplementary Material)
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In this supplementary material we include:(1) Section 1: the statistics of datasets used in the experiments,(2) Section 2: implementation details and performance of the three demographic models trained to label MS-Celeb-1M,(3) Section 3: distributions of the scores

CHILD FACE RECOGNITION SYSTEM USING MOBILEFACENET
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SLM Oo, AN Oo uit.edu.mm Face recognition is a kind of identifying people in image. It matches the database of known faces and input image of unknown face . Deep learning is one of the state-of-art technologies which achieve state-of-art performance on face recognition . In this paper, we develop child