ENGINEERING RESEARCH PAPERS

face recognition research papers 2015 IEEE PAPER




Deep face recognition
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Abstract The goal of this paper is face recognition–from either a single photograph or from a set of faces tracked in a video. Recent progress in this area has been due to two factors:(i) end to end learning for the task using a convolutional neural network (CNN), and (ii) the

Face Recognition Vendor Test (FRVT) Performance of Automated Gender Classification Algorithms
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Facial gender classification is an area studied in the Face Recognition Vendor Test (FRVT) Still Facial Images Track. While peripheral to automated face recognition, it has become a growing area of research, with potential use in various applications. The motivation for

AN EFFICIENT HYBRID REAL TIME FACE RECOGNITION ALGORITHM IN JAVA ENVIRONMENT
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ABSTRACT Image processing on mobile smart phones is a new and exciting field with many challenges due to limited hardware and connectivity problems. Android based mobile phones are now becoming the core of many applications. This paper develops a real time

Face Recognition Difficulties in Children: Hits and/or Correct Rejections
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Face recognition difficulties during childhood are well-documented. However, mixed results were obtained regarding the precise nature of these difficulties using different experimental tasks. Using recognition memory paradigm (learning a set of faces followed by an old/new

Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A
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Abstract Rapid progress in unconstrained face recognition has resulted in a saturation in recognition accuracy for current benchmark datasets. While important for early progress, a chief limitation in most benchmark datasets is the use of a commodity face detector to Abstract:Recognition rate of traditional face recognition algorithm would decline sharply under the condition of variance Gaussian noise. In order to deal with this problem, an algorithm of Pulse Coupled Neural Network (PCNN) combined with linear discriminant

A longitudinal study of automatic face recognition
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Abstract With the deployment of automatic face recognition systems for many large-scale applications, it is crucial that we gain a thorough understanding of how facial aging affects the recognition performance, particularly across a large population. Because aging is a

Elastic Bunch Graph Matching Based Face Recognition Under Varying Lighting, Pose, and Expression Conditions
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ABSTRACT In this paper performance of elastic bunch graph matching (EBGM) algorithm for face recognition under variation in facial expression, variation in lighting condition and variation in poses are given. In this approach faces are represented by labelled graphs.

High-Fidelity Pose and Expression Normalization for Face Recognition in the Wild
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Abstract Pose and expression normalization is a crucial step to recover the canonical view of faces under arbitrary conditions, so as to improve the face recognition performance. An ideal normalization method is desired to be automatic, database independent and high-fidelity,

Face Recognition Using Discrete Orthogonal Hahn Moments
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Abstract:One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work

Contribution of Bodily and Gravitational Orientation Cues to Face and Letter Recognition
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Abstract Sensory information provided by the vestibular system is crucial in cognitive processes such as the ability to recognize objects. The orientation at which objects are most easily recognized the perceptual upright (PU) is influenced by body orientation with

A Maximum Entropy Feature Descriptor for Age Invariant Face Recognition
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Abstract In this paper, we propose a new approach to overcome the representation and matching problems in age invariant face recognition. First, a new maximum entropy feature descriptor (MEFD) is developed that encodes the microstructure of facial images into a set Face alignment is a computer vision technology for identifying the geometric structure of human faces in digital images. Given the location and size of a face, it automatically determines the shape of the face components such as eyes and nose. A face alignment Registered traveler (RT) programs are designed to expedite legitimate travelers through a border control or security screening process by conducting a security threat assessment to determine risk levels prior to acceptance into the program and passage through a

Face Detection and Recognition Technology for HCI based on RBF Neural Network
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Abstract In this paper, feature extraction and facial recognition are studied in order to resolve problems like high-dimension problem, small size samples and no-linear separable problem that exist in facial recognition technology. In the part of feature extraction we use a

Improving Gender Recognition Rate in Face Recognition System Based On Linear Discriminant Analysis Technique
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Abstract: In this paper, we present a face recognition system that is used for identity authentication. An image is given as input to the system by the user; this is matched against the images in the database and identity is resolved. The main metric for the system is the

Sparsity Preserving Discriminant Projections with Applications to Face Recognition
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Dimensionality reduction is extremely important for understanding the intrinsic structure hidden in high-dimensional data. In recent years, sparse representation models have been widely used in dimensionality reduction. In this paper, a novel supervised learning method

Discriminant analysis on Riemannian manifold of Gaussian distributions for face recognition with image sets
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Abstract This paper presents a method named Discriminant Analysis on Riemannian manifold of Gaussian distributions (DARG) to solve the problem of face recognition with image sets. Our goal is to capture the underlying data distribution in each set and thus

The Research of Face Recognition Method Based on Sparse Representation and Feature Selection
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Abstract: Based on the digital image facial recognition technology is as the research background. Based on the analysis of the existing face recognition methods, combining with the latest theory of pattern recognition is for face recognition of facial expression.

Face Granulation using Difference of Gaussian (DOG) Method for Face Recognition
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ABSTRACT In this paper first we represent an overview of face recognition and discuss the methodology and functioning. This paper presents surgically altered robust face recognition based on granular computation and features extraction. Biometrics for person

An Enhanced Method of Face Recognition for Cloud Robot
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Abstract This paper describes a cloud-based robot system which connects cloud computing infrastructure for accessing distributed computing resources and big data and executing multitask like face detection, face recognition and etc. The ROS (Robot Operating system)

Face Recognition Using Fused Spatial Patterns
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ABSTRACT Biometric recognition or biometrics is an automatic recognition system, based on physiological and/or behavioral characteristics of an individual. Biometrics makes it possible to confirm, establish an individual's identity based on who he/she is, instead of

Face recognition based on subset selection via metric learning on manifold
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Abstract With the development of face recognition using sparse representation based classification (SRC), many relevant methods have been proposed and investigated. However, when the dictionary is large and the representation is sparse, only a small

Mechanisms for increasing the efficiency of holistic face recognition systems
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Abstract. In holistic face recognition systems face is represented by set of features derived directly from brightness of 2D image pixels. To ensure proper representation of face under variability in head rotation, lighting and expression many templates should be provided.

Extraction of Hidden Features using Preprocessing Techniques and Texture analysis forFace Recognition
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Abstract: face recognition is the one of the robust technology compared to other biometric technologies. It has a lot of applications such as remote sensing, access control, surveillance systems etc, but it is difficult task under difficult lighting conditions which is

Age Synthesis and Assessment via Face Recognition
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Abstract One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process

Feature selection for 2D and 3D face recognition
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Face recognition is a popular research topic with a number of applications in several industrial sectors including security, surveillance, entertainment, virtual reality, and human- machine interaction. Both 2D images and 3D data can now be easily acquired and used

FACE RECOGNITION BASED ATTENDANCE MANAGEMENT SYSTEM BY USING EMBEDDED LINUX
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Students attendance in the classroom is very important task and if taken manually wastes a lot of time. There are many automatic methods available for this purpose, ie, biometric attendance. All these methods also waste time because students have to make a queue to

Projection metric learning on Grassmann manifold with application to video based face recognition
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Abstract In video based face recognition, great success has been made by representing videos as linear subspaces, which typically lie in a special type of non-Euclidean space known as Grassmann manifold. To leverage the kernel-based methods developed for

Face recognition in schizophrenia disorder: a
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Abstract Facial emotion processing has been extensively studied in schizophrenia patients while general face processing has received less attention. The already published reviews do not address the current scientific literature in a complete manner. Therefore, here we

A Dynamic Security Protocol for Face Recognition Systems Using Seismic Waves
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Abstract:Face recognition system is one of the robust means of authentication. It involves comparing the faces of an individual against a set of images in the training database. Thus the security issues pertaining to the training database is very critical. This paper aims at

Face Recognition Using Particle Filter
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Abstract Multi view face recognition using multiple camera networks is an active research area. The main aim of this paper is to handle different pose variations in multi camera network and recognizing face from those videos. The traditional approaches handle the

Face Recognition in Complex Background: Developmental Network and Synapse Maintenance
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Abstract As an important sub-field in computer vision and pattern recognition, face recognition has important theoretical and practical application. It is a very complicated problem which is often affected by variations in illumination condition, head pose, facial

Computerized Face Recognition in Renaissance Portrait Art
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Abstract:In this work, we explore the feasibility of face recognition technologies for analyzing works of portraiture, and in the process provide a quantitative source of evidence to art historians in answering many of their ambiguities concerning identity of the subject

Real-Time Secure System for Detection and Recognition the Face of Criminals
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Abstract:in this paper We present a system for real-time, saved images And Video Recorded in this three Method We Can detecting and recognizing faces of a criminal at public place Or Checkpoint such that the system easy to learn And to implementation, the

Low-Resolution Video Face Recognition with Face Normalization and Feature Adaptation
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Abstract:Face analysis is a challenging topic, especially when addressing low-resolution data. While face detection is working satisfactorily on such data, further facial analysis often struggles. We specifically address the issues of face registration, face normalization and

Face Recognition System Invariant to Plastic Surgery
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Abstract: The importance of biometric authentication is increasing rapidly because it verifies the claimed user identity. There are different types of biometrics available such as finger print, facial scan, retinal scan, voice print. From these, face is one of the most commonly

Face recognition with deep learning for mobile applications
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Abstract There is a lack of mobile open source applications to search and find selected persons in image libraries. Especially if you do not want to give away your data to cloud based services this paper shows a novel approach to use deep learning to train a feature

Hierarchical-PEP Model for Real-world Face Recognition
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Abstract Pose variation remains one of the major factors adversely affect the accuracy of real- world face recognition systems. Inspired by the recently proposed probabilistic elastic part (PEP) model and the success of the deep hierarchical architecture in a number of visual

Content Based Image Retrieval of Corel Images Along With Face Recognition
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Abstract:: Image Retrieval basically deals with identification of similar images from a large database. Image retrieval based on rich content of the image is known as Content Based Image Retrieval (CBIR). The visual content of an image is analysed in terms of different

Single Sample Face Recognition using LGBP and Locality Preserving Discriminant Analysis
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Abstract: On single sample condition, current face recognition algorithm yields serious performance drop or even fail to work, therefore a face recognition algorithm based on LGBP and locality preserving discriminant analysis (LPDA) was proposed. Image enhancement

A New LBP Method to Improve Face Recognition
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Abstract In this paper, we propose a complete representation, called Multi-scale Block Local Binary Pattern (MB-LBP), and apply it to face recognition. The face recognition process mainly consists of three phase: face representation, feature extraction, and classification.

Learning Modified CS-LBP for Face Recognition
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Abstract: The face of a human being conveys extensive information about the identity and emotional state of the person. However, the most important phase in face recognition is extraction. In which the most useful and unique features of the face image are extracted.

Thermal Face Recognition Using Moments Invariants
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Abstract:Face recognition using different imaging modalities, particularly infrared imaging sensors, has become an area of growing interest. The use of thermal IR images can improve the performance of face recognition in uncontrolled illumination conditions. In this paper,

Learning Multi-channel Deep Feature Representations for Face Recognition
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Abstract Deep learning provides a natural way to obtain feature representations from data without relying on hand-crafted descriptors. In this paper, we propose to learn deep feature representations using unsupervised and supervised learning in a cascaded fashion to

Face Recognition System for Cloud Robot
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Abstract. This paper proposes a face recognition system for RC-Cloud Robot, which connects cloud computing infrastructure. The robot accesses distributed computing resources and big data and executing multitask like face detection, face recognition and

Complete Architecture of a Robust System of Face Recognition
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ABSTRACT Although human face recognition is a hard topic because of the multitude of parameters involved (eg variation in pose, illumination, facial expression, partial occlusions), it is very important to be interested and to invest in it viewed her many fields of application

Achieving Robustness in Face Recognition by Effective Feature Acquisition
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Abstract:In the past few decades, face recognition has been a widely researched topic, since it is a robust means of authentication. Extraction of features from the face images during face recognition is a very challenging task. Hence, proper selection of appropriate

Effects of pose and image resolution on automatic face recognition
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Abstract: The popularity of face recognition systems have increased due to their use in widespread applications. Driven by the enormous number of potential application domains, several algorithms have been proposed for face recognition. Face pose and image resolutions are among

Age Invariant Face Recognition using K-PCA and K-NN on Indian Face Age Database (IFAD)
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ABSTRACT In this paper a comparative analysis of K-Principle Component Analysis (K- PCA) and K-Nearest Neighbor (KNN) classifier is done for age invariant face recognition using Indian Face Age Database (IFAD). IFAD is a real time and wild in face database

Face Recognition System using Local Feature Descriptors: A Survey
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Abstract:Face recognition is evergreen and rapidly growing research field in the area of Artificial Intelligence and Automation, Computer Vision. It is used to finding an individual's identity. There are various methods used to represent a face. In this paper i am going to

Face Recognition Using Principal Component Analysis in MATLAB
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Extended Non-negative Matrix Factorization for Face and Facial Expression Recognition
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Abstract:Face and Facial Expression Recognition is a broad research area for its diversified applicability in different applications from security, surveillance to medical diagnosis. The main challenge in this area is to decrease the recognition time as well as

AN EMPIRICAL STUDY OF THE BEHAVIOR OF A FACE RECOGNITION SYSTEM BASED ON EIGENFACES AND K-NEAREST NEIGHBORS TECHNIQUES
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Abstract-Developing a face recognition computational model is a hard task. Extracting facial features from facial images becomes a hard when the images have different dimensions, especially in the steps of extraction and classification. In this paper, we propose an

ACTIVE APPEARANCE MODEL AND PCA BASED FACE RECOGNITION SYSTEM
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Abstract-At present face recognition has wide area of applications such as security, law enforcement. Imaging conditions, Orientation, Pose and presence of occlusion are huge problems associated with face recognition. The performance of face recognition systems

A Novel Solution to Test Face Recognition Methods on the Training Data Set
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Abstract In modern life, we need better techniques based on biometric features recognition such as face recognition, fingerprint recognition and iris recognition. We present a method which can be used for face recognition or verification applications. The method can solve As a contactless type of biometric identification, it is suitable for applications that require a high level of hygiene or use in public applications. Several banks in Japan have used palm vein authentication for ATM security since July 2004. In addition to Japan, Brazil has also

Evaluation of Performance of the Face Detection Using Skin Colour Model and Face Recognition Using ANN
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Abstract:This paper presented a new and robust algorithm for face detection and recognition using skin colour model with Feed Forward neural Network. Skin colour model is used to detect face of region from given input testing image. After detection, Features are

Modified PCA with Genetic Algorithm for Age Invariant Face Recognition
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Abstract: Security systems based on traditional techniques are more prone to be attacked by hackers and, such major attacks exposed weakness in most sophisticated security systems. A number of supervision agencies are now more motivated to improve security based on

Face Detection Using Skin Colour Model and Face Recognition Using ANN
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Abstract:Face detection is the first basic component of any face processing system. In the last few years, Researchers have shown an interest in the active research area such as Face Detection and recognition system. Face recognition system is used to recognize

Proposing an Enhanced Face Recognition Technique Using Multi-Wavelet Transform
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ABSTRACT Face recognition has been an active research for more than three decades. In general face recognition consists of feature extraction and classification. Principal Component Analysis (PCA) is one of the methods for features extraction under the

An Efficient Approach to Face Recognition Using a Modified Center-Symmetric Local Binary Pattern (MCS-LBP)
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Abstract In this paper, we present a novel face recognition method called Multi-scale block Center-Symmetric Local Binary Pattern (MCS-LBP). The face recognition process mainly consists of three phase: face representation, feature extraction, and classification.

Efficient Face Recognition Technique using PCA in Neural Network
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Abstract: The Security is the main aspect to protect the confidential information from the intruder. The features are initially required for recognize any object. Feature extraction technique is used for extract the face features. Face Recognition is a term to describe the

Face Recognition Based on Non-Negative Factorization and FLDA for Single Training Image per Person
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Abstract: Dimensionality reduction is performed by both Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA). Covariance matrix and Eigen vector approach is followed in PCA. FLDA finds within class and between class scatter matrices.

Face Recognition by Classification using Radial Basis Function
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Abstract The face recognition task involves extraction of unique features from the human face. Manifold learning methods are proposed to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. PCA and LDA

Face Recognition Using Plurality Voting and Collaborative Representation based on the Bit-plane Information.
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Abstract As a new representation technique, collaboration representation is used to represent the test sample with all training samples from all classes. Plurality voting is one of the most widely used combination strategies in pattern recognition. This paper presents a

The Research on the Multiple Kernel Learning-based Face Recognition in Pattern Matching
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Abstract: The paper analyses the multiple kernel learning-based face recognition in pattern matching area. Based on the analysis of the basic theory of multiple kernel SVM, this thesis focuses on the multiple kernel SVM algorithm based on semi-infinite linear program (SILP)

SPARSE REPRESENTATION THEORY AND ITS APPLICATION FOR FACE RECOGNITION
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Abstract-Face recognition aims at endowing computers with the ability to identify different human beings according to their face images. However, recognition rate will decrease sharply when it refers to the non-ideal imaging environments or the incorporation of users,

Face Recognition on Drones: Issues and Limitations
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ABSTRACT Drones, as known as unmanned aerial vehicles (UAV), are aircrafts which can perform autonomous pilot. They can easily reach locations which are too difficult to reach or dangerous for human beings and collect images from bird's-eye view through aerial

Application Expansion inside Optimized RBF Kernel of SVM in Robust Face RecognitionSystem
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Abstract Information is critical in light of the fact that it assists us take a decision. Yet, it needs security. With these worries, picture is the most ideal method for representation of data to to read, write, and and comprehend the data. Face recognition is secure since we can't

Face Recognition based on Deep Neural Network
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Abstract In modern life, we see more techniques of biometric features recognition have been used to our surrounding life, especially the applications in telephones and laptops. These biometric recognition techniques contain face recognition, fingerprint recognition and iris

YCbCr Technique based Human Face Recognition
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Abstract Face detection is a necessary first-step in face recognition systems, with the reason of localize and extract the face region from the background. It also has a number of applications in areas such as content-based image recovery, video coding, video

Mixed error coding for face recognition with mixed occlusions
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Abstract Mixed occlusions commonly consist in real-world face images and bring with it great challenges for automatic face recognition. The existing methods usually utilize the same reconstruction error to code the occluded test image with respect to the labeled

Face Recognition using Edge Detection of Layer
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ABSTRACT Face recognition of people in a crowd is a challenging issue that received much attention during recent scenario attributable to its numerous applications in different fields. The analysis of human crowds has widespread uses from law enforcement to urban

Robust Face Recognition for Uncontrolled Environment
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Abstract The aim of this project is face recognition from constraint environment. In this constraint environment various occlusion, different pose variation are exist. Robust Face recognition is needed today, for constrained environment because it used in ATM access,

Indian Face Age Database: A Database for Face Recognition with Age Variation
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ABSTRACT Face recognition with age variation is a challenging task for researchers. In this research paper a new face database is proposed. The proposed name of this database is Indian Face Age Database (IFAD). It consists of images of Indian celebrities. To enhance

Deep Learning on a Raspberry Pi for Real Time Face Recognition.
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Abstract In this paper we describe a fast and accurate pipeline for real-time face recognition that is based on a convolutional neural network (CNN) and requires only moderate computational resources. After training the CNN on a desktop PC we employed a

Blurred 2D Face Restoration and Recognition Using Artificial Neural Network
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Abstract Recognizing Human faces from images taken by digital camera is a challenging task because these faces are usually still and corrupted by various noises and blurring effects. The performance of face recognition system collapse significantly when blurred

Face Recognition Techniques-An evaluation Study
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Face recognition is the ability of categorize a set of images based on certain discriminatory features. Classification of the recognition patterns can be difficult problem

Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP
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Abstract The characteristics of human body parts and behaviour are measured with biometrics, which are used to authenticate a person. In this paper, we propose Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP. The face

Face Recognition Using Approximated Bezier Curve and Supervised Learning Approach.
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Abstract Bezier curve are very strong for variety of application. Specifically in image processing it applies to object recognition, face recognition, and human gait recognition. It also works on fingerprint and other biometric system recognition. This paper presents a

FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS AND GABOR FILTERS.
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ABSTRACT: The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to

Face Recognition and Template Protection with Shielding Function
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Abstract Biometric authentication is the use of unique human features to provide a secure, reliable and convenient access to an environment or a computer system. However, there are numerous security and privacy concerns associated with the use of biometrics as a means

An Efficient Approach for Human Face Recognition
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Abstract-Face recognition is one of the important fields for their wide range of applications in different areas. Our job is to implement an efficient approach for human face recognition. This paper presents an efficient approach to address the representation issue and the

Face Recognition Using String Grammar Nearest Neighbor Technique
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Abstract:Face recognition has become one of the important biometrics in many applications. However, there is a problem of collecting more than one image per person in the training data set, the so-called one sample per person problem. Hence in this paper,

Analysis of Faces Using Supervised and Unsupervised Neural Network for 3D Face Recognition
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Abstract: Soft computing based different methods are largely being applied in diverse areas of the research world. Face recognition being one of the major streams of Biometrics is going through huge research around the globe. In this paper, the experimental results for

MULTIPLE FACE DETECTION RECOGNITION
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Abstract:This paper describes the design and construction of a test-bed for prototyping of embedded face detection and recognition algorithms. The embedded device has a processor, camera, colour display, and wireless networking. Eigen faces approach for

Support Vector Machines for Face Recognition
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Abstract:The computer vision has become an emerging domain for machine learning ways. In the last decade, face recognition are developed for the image area to achieve correct and speedy performance. Now the face recognition technology (FRT) is in much

Weighted Feature-Level Fusion of Color Local Texture Features for Face Recognition
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Abstract:This paper presents an extension of the framework proposed by Choi et al. that uses color local texture features (CLTF) for face recognition. The original framework combines multiple CLTFs, each of which corresponds to the associated color channel,

Face Recognition Using PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) Techniques
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Abstract: image processing field is becoming more popular for the security purpose in now days. It has many sub fields and face recognition is one from them. Many techniques have been developed for the face recognition but in our work we just discussed two prevalent

Comparative Study of Face Recognition Classifier Algorithm
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Abstract. On the basis of the analysis of characteristics, application occasion, and limitations, comparison simulations are performed with the combined methods by means of ATT face database. The paper present the method based on PCA and FLDA which can improve

An Overview of Face Recognition Schemes
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Abstract A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial

A New Feature Descriptor for Face Recognition
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ABSTRACT The idea behind this paper is to use a new statistical feature for the face recognition problem. To the best of our knowledge, no one has attempted to implement this approach before. The idea is simple and straight forward. For each face image, a feature

Face Recognition based on GSVD
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ABSTRACT The task of face recognition has been actively researched in recent years because of its many applications in various domains. This study suggested new and novel method to matching the input face image with face images in database based on GSVD.

Face Recognition based on Improved Robust Sparse Coding Algorithm
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Abstract In order to improve the performance of face recognition, a novel face recognition method based on improved robust sparse coding algorithm (MRCS-ELM) to solve the defecting of traditional sparse coding algorithm. Firstly, the face images are collected and

FACE RECOGNITION TECHNIQUES AND APPROACHES: A SURVEY
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ABSTRACT: Face recognition is a necessity of the modern age as the need for identification of individual has increased with the globalization of the world. Personal authentication through face has been under research since last two decades. The performance of the

Automatic face recognition in digital world
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Abstract:Digital images have become prevalent, through the spread of surveillance cameras, smart phones, and digital cameras. Economical data storage has led to enormous online databases of facial images of identified individuals, such as licensed drivers,

Application in Face Recognition Based on Improved Local Linear Embedding Algorithm and Artificial Vector Machine
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Abstract In order to improve the accuracy of face recognition in a variety of gestures, a face recognition method of improved local linear embedding algorithm is proposed. First, facial features are extracted by Gabor transform and then dimensions of the facial features are

The Cambridge Mindreading Face-Voice Battery for Children (CAM-C): complex emotionrecognition in children with and without autism spectrum conditions
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Abstract Background: Difficulties in recognizing emotions and mental states are central characteristics of autism spectrum conditions (ASC). However, emotion recognition (ER) studies have focused mostly on recognition of the six 'basic'emotions, usually using still

A Novel Algorithm for Face Recognition From Very Low Resolution Images
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Abstract Face Recognition assumes much significance in the context of security based application. Normally, high resolution images offer more details about the image and recognizing a face from a reasonably high resolution image would be easier when Abstract:This demo shows a working prototype of the 3D face recognition biometric device utilizing a low-cost depth sensor, namely SoftKinetic DS325. It is based on the Intel Celeron

A New Discrete Cosine Transform on Face Recognition through Histograms for an Optimized Compression
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ABSTRACT Images with reduced signal level that can be easily stored in a database for recognition purposes are highly demanded. A system with large capacity requires a highly compressive technique for its efficiency. In this study, more efficient image compression

Face Recognition of Illuminated Images Using Dwt and Pca
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Abstract The look of a face image is severely affected by illumination conditions that obstruct the routine face recognition process. To recognize faces under varying illuminations, we have proposed a 2D wavelet-based normalization method so as to normalize

Face Recognition: A Tutorial on Computational Aspects
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ABSTRACT Face recognition is a sophisticated problem requiring a significant commitment of computer resources. A modern GPU architecture provides a practical platform for performing face recognition in real time. The majority of the calculations of an eigenpicture

Face Recognition Model for Age Invariant
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Abstract In this paper we design and implement a new model to recognize images for human face for age invariant by using the Scale Invariant Feature Transform (SIFT) algorithm. The proposed model transform an image into a large collection of local feature

Human Face Recognition Based on PCA Method using MATLAB
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Abstract-Face recognition is very hot bold topic from a number of years because of its application. Principle Component Analysis is a statistical method used for reducing the number of variables in feature extraction and face recognition. It is one of the most

A COMPENDIUM OF PATTERN RECOGNITION TECHNIQUES IN FACE, SPEECH AND LIE DETECTION
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ABSTRACT Lie is a false statement made with deliberate intent to deceive, this is intentional untruth. People use different technologies of lie detection as Pattern recognition is a science to discover if an individual is telling the truth or lying. Patterns can describe some

Pose-Robust Recognition of Low-Resolution Face Images
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Abstract: Face recognition is one of the most successful applications in the field of image processing. Most robust face methods are difficult to improve their performance under certain environments. The paper proposes a method for robust face recognition and

Face Recognition for Partial Occluded Image: A Survey
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Abstract: Over the years biometrics has gained unparalleled popularity in digital medium and has proven its usefulness for several applications concerned with the threats and crime or security purposes. Face Recognition is a widely emerging biometric for automating the

Face Recognition System for Blur Image Using Backpropagation Neural Networks Approach and Zoning Features Extraction Method
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Abstract: Applications of face recognition systems have been fairly well-established. However, since Facial Image Recognition System basically depends on the source images as object recognition and methodology, good analysis results from abnormal images

A LITERATURE SURVEY ON VARIOUS ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION WITH FUZZY K NEAREST NEIGHBOUR
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Abstract The face recognition is popular in video surveillance, social networks and criminal identifications nowadays. The performance of face recognition would be affected by variations in illumination, pose, aging and partial occlusion of face by Wearing Hats,

Face Recognition Algorithm Based on Improved BP Neural Network
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Abstract Face recognition has received wide concern as a hot direction in recognition models. Due to a strong self-adaptive and mapping ability, traditional BP algorithm occupies certain advantages in face recognition, but is has the shortcomings of fast convergence

A Review on Techniques of Illumination in Face Recognition
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A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. It is

on Choosing the Highest Principal Features and the Number of Hidden Neurons in Principal Component Analysis-Artificial Neural Network Face Recognition
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ABSTRACT With fast evolving technology, it is necessary to design an efficient security system which can detect unauthorized access on any system. It s needed to implement an extremely secure, economic and perfect system for face recognition that can protect

IMPROVED FACE RECOGNITION USING ICP TECHNIQUES INCAMERA SURVEILLANCE SYSTEMS
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Face Recognition is important task in real time biometric systems. The main difficult problem in the image processing field is Face recognition. Pose and expressions are the most important challenges among the various factors that control the Face recognition. Pose

PCA Based Face Recognition and Facial Expression Identification System
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Abstract: The face is our primary focus of attention in social intercourse, playing a major role in conveying identity and emotion. We can recognize thousands of faces learned throughout our lifetime and identify familiar faces at a glance even after years of separation. This skill

Face Expression Recognition Based on Motion Templates and 4-layer Deep Learning Neural Network
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Abstract A human facial expression is the formation of facial muscle movement. In our previous research, we proposed a method of identifying facial muscle movement which based on motion templates and GentleBoost. But the method was not robust enough to

Face Facial Expression Recognition System for Human Machine Interaction
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Abstract:-. Face and facial expression recognition system is a natural biological features recognition technology. It is a non intrusive type of technology. This technology automatically identifies and verifies individual face. Thus face and emotion recognition offers one of the

Speaker Recognition For Speech Under Face Cover
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Abstract Speech under face cover constitute a case that is increasingly met by forensic speech experts. Wearing face cover mostly happens when an individual strives to conceal his or her identity. Based on the material of face cover and the level of contact with speech

Face Recognition System: Adaboost and 2DFLD
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Abstract:In this paper the concept of face recognition technologies are presented. As the face system is totally nonintrusive, it can therefore make an existing security system more effective without bothering the user in any way. Automated system for human face



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