free research papers-face recognition




Face Recognition using the most Representative Sift Images.
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Abstract In this paper, face recognition using the most representative SIFT images is presented. It is based on obtaining the SIFT (SCALE INVARIANT FEATURE TRANSFORM) features in different regions of each training image. Those regions were obtained using

Results from evaluation of three commercial off-the-shelf face recognition systems on Chokepoint dataset
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Abstract This report is a supplement to Division Report 2014-27 (TR)''Evaluation methodology for face recognition technology in video surveillance applications (by E. Granger and D. Gorodnichy)[1]. It presents complete evaluation results of three

Subtasks of unconstrained face recognition
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ABSTRACT Unconstrained face recognition remains a challenging computer vision problem despite recent exceptionally high results (~ 95% accuracy) on the current gold standard

A survey: face recognition techniques under partial occlusion.
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ABSTRACT Systems that rely on face recognition biometric have gained great importance ever since terrorist threats imposed weakness among the implemented security systems. Other biometrics ie, fingerprints or iris recognition is not trustworthy in such situations whereas

An Efficient Hybrid Face Recognition Algorithm Using PCA and GABOR Wavelets
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Abstract With the rapid development of computers and the increasing, mass use of high-tech mobile devices, vision-based face recognition has advanced significantly. However, it is hard to conclude that the performance of computers surpasses that of humans, as humans

Face Recognition using Adaptive Margin Fisher's Criterion and Linear Discriminant Analysis
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ABSTRACT Selecting a low dimensional feature subspace from thousands of features is a key phenomenon for optimal classification. Linear Discriminant Analysis (LDA) is a basic well recognized supervised classifier that is effectively employed for classification. However,

Face Recognition System using Template Method
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Abstract Face Recognition is a Biometric Application, which is used for Criminal Identification, Visitor Verification and many other Real Time Identification systems. We use basically two approaches for this system which are namely 'Template Matching'and '

Experience matters: Modeling the relationship between face and object recognition
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Abstract Some research has suggested that face and object recognition are independent abilities. Recently, however, it has been shown that they are not, and that the relationship is moderated by experience with the object categories (Gauthier et al., in press). Gauthier et

Evaluation of Surgical Outcomes for Ptosis Surgery by Face Recognition Software.
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Purpose: This study was aimed to use the age estimation segment of face recognition software to determine whether patients appeared younger after surgery for aponeurotic ptosis and dermatochalasis. Design: This is a prospective interventional case series.

Comparative Analysis of advanced Face Recognition Techniques
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ABSTRACT This project entitled Comparative analysis of advanced Face Recognition Techniques , it is based on fuzzy c means clustering and associated sub neural network. It deals with the face is a complex multidimensional visual model and developing a

A Survey on Face Detection and Recognition Approaches
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Abstract Face detection and recognition are major concerns in the area of biometric based security systems and purposes. These processes must ensure the recognition accuracy and minimum processing time. In this paper a review of existing face detection and recognition

Synthesis-based Robust Low Resolution Face Recognition
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ABSTRACT Recognition of low resolution face images is a challenging problem in many practical face recognition systems. Methods have been proposed in the face recognition literature for the problem which assume that the probe is low resolution, but a high

Real Time Face-Recognition Based Attendance Generation and Perception Level Extraction
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ABSTRACT Automatic face recognition and utilization of facial expressions is fast becoming an area of heightened interest in research oriented fields such as machine vision and creation of smart, artificially intelligent systems. In this paper we present the application of these

Study of Face Recognition Techniques
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Abstract A study of both face recognition and detection techniques is carried out using the algorithms like Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA), Linear Discriminant Analysis (LDA) and Line Edge Map (LEM). These algorithms

An Integrated Face Recognition Algorithm Based on Wavelet Subspace
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ABSTRACT In this paper, based on the study of the Two-Dimensional Principal Component Analysis (2DPCA), Two-Dimensional Principal Component Analysis (2DPCA) and fuzzy set theory, we propose a integrated face recognition algorithm based on wavelet subspace.

Human Face Recognition and Face Detection using Skin Colour Model
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Abstract As one of the most successful applications of image analysis and understanding, face recognition has recently gained significant attention, especially during the past several years. Human face recognition play important roles in many applications such as video

Eigen-Pep for Video Face Recognition
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Abstract. To effectively solve the problem of large scale video face recognition, we argue for a comprehensive, compact, and yet flexible representation of a face subject. It shall comprehensively integrate the visual information from all relevant video frames of the

Face Recognition Using PCA Technique
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Abstract This paper provides the information about Face Recognition Technology which gives the much more security in the field of multimedia and information technology. To provide the protection to the data we keep the password but as we know hackers can

Illumination Invariant Novel Approaches for Face Recognition
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ABSTRACT Most of current identification and verification systems like access control and surveillance require reliable person identification technique. The primary goal of such systems is that resources are accessed only by legitimate users. Inefficient person

Wavelet Subspace Based Integrated Face Recognition Scheme
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Abstract In this paper, based on the study of the Two-Dimensional Principal Component Analysis (2DPCA), Two-Dimensional Principal Component Analysis (2DPCA) and fuzzy set theory, we propose a integrated face recognition algorithm based on wavelet subspace.

Implementation of Plastic Surgery Face Recognition Using Multimodal Biometric Features.
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ABSTRACT Plastic surgery procedures provide a proficient and enduring way to enhance the facial appearance by correcting feature anomalies and treating facial skin to get a younger look. When an individual undergoes plastic surgery, the facial features are reconstructed

Survey of commercial technologies for face recognition in video
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ABSTRACT This report reviews commercial off-the-shelf (COTS) solutions and related patents for face recognition in video surveillance applications. Commercial products are analyzed using such criteria as processing speed, feature selection techniques, ability to perform

AUTOMATIC HUMAN FACE RECOGNITION USING MULTIVARIATE GAUSSIAN MODEL AND FISHER LINEAR DISCRIMINATIVE ANALYSIS.
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ABSTRACT Face recognition plays an important role in surveillance, biometrics and is a popular application of computer vision. In this paper, color based skin segmentation is proposed to detect faces and is matched with faces from the dataset. The proposed color based

Face Recognition Performance Comparison of Fake Faces with Real Faces in Relation to Lighting
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ABSTRACT Face Recognition is widely used in security systems, such as surveillance, gate control systems, and guard robots, due to their user friendliness and convenience compared to other biometric approaches. Secure face recognition systems require advanced

Face Recognition using Neuro-Fuzzy Inference System.
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ABSTRACT Face recognition is the process of identifying one or more people in images or videos. It is an important part of biometric, securitysurveillance system, and image indexing systems. Various face recognition techniques have been proposed in literature

Face recognition based on multi-wavelet and sparse representation
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ABSTRACT. The feature dimension and redundancy can reduce the face recognition speed and rate, the shading and light changing can heavily affect the face recognition effect. So the first key to face recognition is how to effectively extract face features because the face image

Face Recognition Using Artificial Neural Network
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ABSTRACT This paper proposed a noble face recognition algorithm which integrates the principal component analysis; back propagation neural network (BPNN) and discrete cosine transform to improve the performance of face recognition. A whole face recognition system

Improve anti-spoofing performance of face recognition-based identity authentication system by real-time facial expression recognition [J]
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ABSTRACT Face recognition technology has been applied extensively in many fields, such as biometric authentication. However, its application is not widely popularized since its anti- spoofing performance is very deficient. A real-time facial expression recognition algorithm

FACIAL FEATURE EXTRACTION TECHNIQUES FOR FACE RECOGNITION
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ABSTRACT Face recognition is one of the biometric techniques used for identification of humans. The design of the face recognition system includes two basic steps. The first step is the extraction of the image's features and the second one is the classification of patterns.

DETECTION AND RECOGNITION OF HUMAN FACE USING ANN TRAINED BY GENETICAL ALGORITHM
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ABSTRACT A novel face detection system is presented in this paper. Finding faces in an arbitrary scene and successfully recognizing them have been active topics in Computer Vision for decades. Human skin color is an effective feature used to detect faces, although

A Distributed Face Recognition Framework Based on Data Fusion.
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ABSTRACT To accomplish face recognition more efficiently, a distributed face recognition framework based on MB-LBP features and data fusion is presented in this paper. Firstly, four face regions are interactively marked and the Multi-scale Block Local Binary Patterns are

Development of a Student Attendance Management System Using RFID and Face Recognition: A Review
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ABSTRACT Whole world and administrators of Educational institutions' in our country are concerned about regularity of student attendance. Student's overall academic performance is affected by the student's present in his institute. Mainly there are two conventional

A Face Recognition Algorithm Based on Contextual Constraints Generalized Two-Dimensional FLD
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In this paper, an improved subspace learning method using contextual constraints based linear discriminant analysis (CCLDA) is proposed for face recognition. CCLDA first transforms an image matrix to a vector which causes huge dimensionality and

Face Recognition Vendor Test (FRVT)
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Facial age estimation is an area of study new to the Face Recognition Vendor Test (FRVT) with Still Facial Images Track. While peripheral to automated face recognition, it has become a growing area of research, given its potential use in various applications. The motivation

LOCAL TEXTURE DESCRIPTION FRAMEWORK FOR TEXTURE BASED FACE RECOGNITION.
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ABSTRACT Texture descriptors have an important role in recognizing face images. However, almost all the existing local texture descriptors use nearest neighbors to encode a texture pattern around a pixel. But in face images, most of the pixels have similar characteristics

Survey of academic research and prototypes for face recognition in video
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ABSTRACT This report surveys work done by academia in developing Face Recognition solutions for video-surveillance applications. We present an architecture of a generic system for face recognition in video and review academic systems reported in the academic

Face Recognition Based on Improved Neighborhood Maximum margin
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ABSTRACT. In this paper, we proposed face recognition based on improved neighborhood maximum margin. The algorithm builds the k-nearest neighbor graph between the data points. Then assigns completely distinct weights for the interclass and intraclass

Review and Implementation of High-Dimensional Local Binary Patterns and Its Application toFace Recognition
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ABSTRACT High-dimensional local binary patterns [5] have been proved to be a useful feature for face recognition, which provides near-human performance in a widely used face verification benchmark. In this report, we first review the technical aspect of this promising In this paper, a fully automatic framework is proposed for 3D face recognition and its superiority performance is justified by the FRGC v2 data. For 3D data preprocessing, a new face smoothing method is proposed. Meanwhile, 3D facial representation, which is

Face Recognition Based Attendance Marking System
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ABSTRACT Automatic face recognition (AFR) technologies have seen dramatic improvements in performance over the past years, and such systems are now widely used for security and commercial applications. An automated system for human face recognition in a real time

Face Recognition using Eye Distance and PCA Approaches
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ABSTRACT Nowadays, Face Recognition is one of the most popular topics in Image Processing and Computer Vision. This heightened popularity is because of its non- intrusiveness, userfriendliness and immense application in fraud detection, law

Effective Face Recognition Through Color Local Texture Features
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ABSTRACT The new color local texture features that means Color Local Gabor Wavelets (CLGWs) and Color Local Binary Pattern (CLBP), for the purpose of Face Recognition (FR). This method is able to provide excellent recognition rates for face images taken under

Interval Type-2 Fuzzy Logic to the Treatment of Uncertainty in 2D Face Recognition Systems
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ABSTRACT Uncertainty is an intrinsic part of intelligent systems used in face recognition applications. The use of new methods for handling inaccurate information about facial features is of fundamental importance. This paper deals with the design of intelligent 2D

CPU/GPGPU/HW comparison of an Eigenfaces face recognition system
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During the last fifteen years, many electronic devices have been provided with powerful processing units, while at the same time they included power consumption reduction techniques as complex as having variable clock frequency or the ability to enable and

A DCT-based Multimanifold face recognition method using single sample per person
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ABSTRACT One of the major drawbacks of the appearance-based face recognition methods is that they fail to work for face recognition from single sample per person (SSPP). In this paper, a new face recognition method based on the discriminative Multimanifold analysis (

Face Recognition Method Using Improved Discriminant Sparse Preserving Projection
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ABSTRACT. According to the question that sparse preserving projection can't make full use of local structure information of the similar and heterogeneous samples, proposed a face recognition method using improved discriminant sparse preserving projection. It used

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

Multimodal Approach for Face Recognition using 3D-2D Face Feature Fusion
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ABSTRACT 3D Face recognition has been an area of interest among researchers for the past few decades especially in pattern recognition. The main advantage of 3D Face recognition is the availability of geometrical information of the face structure which is more or less

Dimensionality Reduction Based on Supervised Slow Feature Analysis for Face Recognition.
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ABSTRACT Slow feature analysis (SFA) is motivated by biological model to extracts slowly varying feature from a quickly varying input signal. However, traditional slow feature analysis is an unsupervised method to extract slow or invariant feature and cannot be directly

SMART SURVEILLANCE SYSTEM FOR FACE RECOGNITION
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ABSTRACT Smart surveillance system refers to video level processing techniques for identification of unwanted (terrorist) faces from real time video. Video object segmentation is an important part of real time surveillance system. For any video segmentation algorithm

Face Recognition Algorithms Based on Orthogonal Sparse Preserving Projections of Kernel.
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ABSTRACT According to the error approximation problem the sparse preserving projections (SPP) reconstruct the original sample. This paper proposes the algorithms based on orthogonal sparse preserving projections of kernel. In order to get sparse representation To improve the performance of infrared face recognition for time-lapse data, a new construction of blood perfusion is proposed based on bio-heat transfer. Firstly, by quantifying the blood perfusion based on Pennes equation, the thermal information is converted into Student Monitoring By Face Recognition System

Improved LDA and LVQ for face recognition
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ABSTRACT We present a hybrid face recognition algorithm which is based on the linear discriminant analysis (LDA) improved by a fusion technique and learning vector quantization (LVQ) in the paper. Firstly, the improved LDA is utilized to reduce the sample vector

3D Face Recognition from Range Images Based on Curvature Analysis
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ABSTRACT In this paper, we present a novel approach for three-dimensional face recognition by extracting the curvature maps from range images. There are four types of curvature maps: Gaussian, Mean, Maximum and Minimum curvature maps. These curvature maps are

Digital Image Technique using Gabor Filter and SVM in Heterogeneous Face Recognition
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ABSTRACT The main reason for the decrease in changes in appearance of the user is due to the factors such as ageing, beard growth, sun tan. Heterogeneous face recognition involves matching two face images from alternate imaging aesthetic forms, such as an

Movie2Comics: An Effective script face mapping through PCA based face recognition
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ABSTRACT Comics is a very popular graphical medium which conveys a story in terms of a series of cartoon pictures. Converting Movie to Comics automatically includes integration of various automatic methods. They are script-face mapping in which faces of characters

Smart Attendance using Face Recognition with Percentage Analyzer
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ABSTRACT Smart Attendance system is a smart way of marking attendance. It replaces the old hectic and time consuming methods of marking attendance by a smart way which makes use of face recognition technique for marking attendance. In our work we have introduced a

Human Face Recognition by Using Image Coding
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ABSTRACT This paper describes of convert front human face to image coding and histogramof pixel position to provide a measure for automatic face recognition. The edge of face image are detected by using canny algorithm, Then image code algorithm are used to transform Feature based face recognition algorithms are computationally efficient compared to model based approaches. These algorithms have proved themselves for face identification under variations in poses. However, the literature lacks with direct and detailed investigation of

Robust Human Face Recognition in Wavelet Transform based compressed domain
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ABSTRACT Face Recognition has attained much focus over the years as one of the effective applications of Computer Vision and Image Processing. In this paper, we explore the possibility of implementing face recognition systems directly into compressed domain. A

FACE RECOGNITION ALGORITHM BASED ON ORIENTATION HISTOGRAM OF HOUGH PEAKS.
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ABSTRACT In this paper we propose a novel face recognition algorithm based on orientation histogram of Hough Transform Peaks. The novelty of the approach lies in utilizing Hough Transform peaks for determining the orientation angles and computing the

Face Recognition Using Wavelets Transform and 2D PCA by SVM Classifier
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ABSTRACT Among the various biometric methods, face recognition has become one of the most challenging tasks in the pattern recognition field during the past decades. An integrated algorithm for face recognition is proposed based on the respective advantages

FACE RECOGNITION USING PCA AND EIGEN FACE APPROACH
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ABSTRACT In this paper an approach to the detection and identification of human faces is presented and then recognizes the person by comparing characteristics of the face to those of known individuals is described. A face recognition system using the Principal

Sparse Kernel Principal Components Analysis for Face Recognition in RGB Spaces.
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ABSTRACT This paper presents a kinds of information fusion algorithm based on multi-channel color image. The color face image is first separated into three pseudo grayscale images: R, G, and B, then the partial characteristics of face is extracted by use of Gabor wavelet

Research on Information Engineering with Information Technology for E-Learning Based on Face Recognition
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ABSTRACT. As the technology further mature and improvement of social perception, face recognition technology will be applied in more fields. This paper apply the new technology human face recognizing to E-Learning, The realization of this system can make up for the

Face Recognition Using Opencl
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ABSTRACT Face recognition is the biometric identification of human's face and matching the image against a library of known faces. The algorithm used to simulate the above is Eigen faces algorithm. The software which is been proposed to implement is OpenCL. OpenCL (

Random subspace support vector machine ensemble for reliable face recognition
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Face recognition still meets challenges despite the progresses made. One of less addressed problems is to reject unregistered subjects. Aiming to tackle this problem, this paper proposes random subspace support vector machine (SVM) ensemble to provide

face recognition with PCA Algo trained by wavelet



Human face recognition using PCA on wavelet subband
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12. A. Samal, ''Minimum resolution for human facedetection and iden- tification,'' Proc. SPIE 1453, 81–89 1991. 13. A. Samal and PA Iyengar, ''Automatic recognition and analysis of human faces and facial expressions: A survey,'' Pattern Recogn. 25, 65–77 1992. 14.

Face recognition with local binary patterns
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For instance, our method achieved a recognition rate of 97% in the case of recognising faces under different facial expressions (fb set), while the bestThe relatively poor results on the fc set confirm that illumination change is still a challenge to facerecognition.

Computational and performance aspects of PCA-based face-recognition algorithms
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and Sirovich (1990) applied PCA to representing faces and Turk and Pentland (1991) extended PCA to recognizingfaces.1972), Jolliffe (1986), or Valentin et al (1994).] In a PCA-based face-recognitionalgorithm, the input is a training set, t1 tN of N facial images such

Face recognition from a single image per person: A survey
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In the experiment, we fix the testing face but vary the number of trainingfaces for each person. (1). Holistic methods: These methods identify a face using the whole face image as input.(2) Local methods: These methods use the local facial features for recognition.

A review on Gabor wavelets for face recognition
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Six possible cases for facerecognition processes are analyzed and results are listed for each case respectivelyfrontal view faces were used for testing [30], neutral frontal view faces (fa) were used as the model gallery and frontal view faces with different facial expression (fb

Face recognition: A literature survey
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More recently, detection of faces under rotation in depth has been studied. One approach is based on training on multiple- view samples [Gu et al.Many facerecognition sys- tems need facial features in addition to the holistic face, as suggested by studies in psychology.

Face recognition by applying wavelet subband representation and kernel associative memory
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also demon- strated that: 1) the effect of different facial expressions can be atIII. KERNEL ASSOCIATIVE MEMORY AS COMPUTATIONAL MODEL OF FACES In this section, we will briefly some autoassociative memory models which can be readily applied to face recogni- tion.

Discriminant waveletfaces and nearest feature classifiers for face recognition
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to NFP and NFS where the feature planes and spaces were respectively spanned to cover wide facial variations for[11] AJ Goldstein, LD Harmon, and AB Lesk, Identification of Human Faces, Proc.[14] SH Lin, SY Kung, and LJ Lin, FaceRecognition/Detection by Probabilistic

Classifying facial attributes using a 2-d gabor wavelet representation and discriminant analysis
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M. Lyons, J. Budynek, and S. Akamatsu Automatic Classification of Single Facial Images, IEEE Morikawa, and S. Akamatsu A linked aggregate code for processing faces, Pragmatics and Wiskott, J. Fellous, N. Krüger, and C. von der Malsburg, FaceRecognition and Gender

Gabor-based kernel PCA with fractional power polynomial models for face recognition
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images used in our experiments (cropped to the size of 128 Â 128 to extract the facial regionThe top face image is a test image and NNC denotes a nearest neighbor to the mean classifierThe five images in the middle are the mean faces of the five pose classes derived from the

Gabor-based kernel PCA with doubly nonlinear mapping for face recognition with a single faceimage
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B. FaceRecognition Under Normal Conditions The respective performances of several face recognition methods based on the normal faces from theGW+PCA means using Gabor rep- resentations as the facial features, and then adopting PCA to reduce the feature

Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition
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a Gabor wavelet based elastic bunch graph matching method to label and recognize human faces.matching [21], [38] or manual annotation of 34 points on every face image [26 wavelet representation gives better performance than other techniques for classifying facial actions.

Multiresolution face recognition
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The images that contain neutral facial expression are put in the training set.11. Sample face images containing changes in expression first row from CMU PIE, second row from FERETFor faces subject to expression changes only, we found out that performing PCA or ICA1 on

Automatic eye detection and its validation
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J. Gemmell, K.Toyama, and V. Kruger, Hierarchical wavelet networks for facial feature localization Martinez, Recognizing imprecisely localized, partially oc- cluded, and expression variant faces from aJ.-M.Fellous, N. Kruger, and C. von der Malsburg, Facerecognition by elastic

An improved PCA face recognition algorithm based on the discrete wavelet transform and the support vector machines
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of facerecognition; it compares the face images which are needed to be recognized with theAnd the SVM classifier commonly used nowadays can gain higher recognition rate than the traditional wavelet transform has been introduced to do the preprocess of the face images to

Recognition of facial expressions using Gabor wavelets and learning vector quantization
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to some other expression, no feature based classification technique can correctly classify both of the faces.Tungsten lights were positioned to create an even illumination on the face.to find out if that length for feature vector is sufficient for correct recognition of facial expressions

A novel incremental principal component analysis and its application for face recognition
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ZHAO et al.: A NOVEL INCREMENTAL PCA AND ITS APPLICATION FOR FACERECOGNITION 875where S2 is of size m × r and S3 is of size r × r. Due to the high dimensionality of the face image, wherein S1 and S are often singular, we develop the incremental-learning

Comparison between geometry-based and gabor-wavelets-based facial expressionrecognition using multi-layer perceptron
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[4] R. Chellappa, C. Wilson, and S. Sirohey. Human and ma- chine recognition of faces: A survey. Automatic interpreta- tion and coding of face images using flexible models.A neural network approach to component versus holistic recognition of facial expressions in images.

A discriminative feature space for detecting and recognizing faces
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A novel discriminative feature space was proposed which is efficient not only for facedetection but also forinto an enhanced feature histogram, both shape and texture information of the facial image.we trained a 2nd degree polynomial kernel SVM to detect frontal faces in gray

Independent component analysis of Gabor features for face recognition
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is used here to derive independent Gabor features found useful for the recognition of human faces.In order to extract the facial region, the images are normalized to the size of 128400 images from the ORL database are used to eval- uate the facerecognition performance of

Eigenfaces for recognition
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(2016) Recognizingfaces with normalized local Gabor features and(2016) A facerecognition system based on convolution neural network using multiple distance face. Soft Computing.(2016) Task-dependent multi-task multiple kernel learning for facial action unit detection.

Gabor wavelets and general discriminant analysis for face identification and verification
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within each super-state describe in more detail each of the facial regionsAnalysis (ICA) [6] have had a significant influence within the facerecognition community forEigenfaces are a set of eigenvectors arising from applying PrincipalComponentAnalysis (PCA) to a collection of

Face recognition across pose: A review
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USF-3D database contains 136 3D face scans with facial textures, which can be rotated to render as many poses as the experiment requires.ORL database contains 10 poses within20° per face of 40 faces, Bern University database contains 5 poses within20° per face of

Combinational method for face recognition: wavelet, PCA and ANN
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[2] G. Chow and X. Li, "Towards a system for automatic facial feature detection 22] D. Valentin, H. Abdi and AJ O'Toole, "Principal component and neural network analyses of face images: Explorations into the nature of information available for classifying faces by sex

Wavelet-based FLD for face recognition
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images of low and mid-range frequency bands are trained and used to recognize faces.matrix such as variation caused by illumination, facial expression, wearing3. WAVELETBASED FLD ALGORITHM The facerecognition system based on eigenfaces consists of training

Face recognition using transform features and neural networks
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References. 1. R Chellapa, CL Wilson, S Sirohey; Human and machine recognition of faces: A survey. Proc.4. B Moghaddam, T Starner; View-based and modular eigenfaces for face recognition. Proc. IEEE Conf.Int. J. Pattern Recognition Artif. Intell., 7 (4) (1993), pp. 775–782.

Face Recognition based on haar wavelet transform and principal component analysisvia levenberg-marquardt backpropagation neural network
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Some samples of images from this database is shown in Fig. 2. These face images varies in facial expression and illumination.30 Figure 2: Sample images of Face94/Dr Libor Spacek Faces Directories. The proposed facerecognition method shown in Fig.

Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance
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wavelet-based elastic bunch graph matching method to label and recognize human faces.an algorithm for two-class categorization of gender, race, and facial expres- sion.showed that the Gabor image representation yielded better performance for facerecognition than other

Subspace linear discriminant analysis for face recognition
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In the feature-based approach, many systems have been developed in which wavelets play a key role in facial image representation, including Gabor `jets' 26The basic purpose of face recognition is to distinguish persons via their face images; thus di erent faces of the

A survey of face recognition techniques.
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utilize tools such as neural networks and machine learning techniques to recognize faces.The facial features are selected by obtaining Local Binary Pattern (LBP) [160] histograms of one-against-one approach [163] for decomposing the multi-class facerecognition problem into

Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft k-NN ensemble
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B. Experiments on the AR Database The AR face database [44], [45] contains over 4000 color face images of 126 people's faces (70 men and 56 women), including frontal view faces with different facial expressions, illumination conditions, and occlusions (sun glasses

The CAS-PEAL large-scale Chinese face database and baseline evaluations
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On the other hand, in a partially automatic mode, the precise facial landmark locations are directions Wopt that maximize the total scatter across all images of all faces in theTypically, in facerecognition application, the number N of training images is much smaller than the

Learning multi-scale block local binary patterns for face recognition
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To dispense the need for a training process for faces of a newly added person2. Experiment 1 is designed to measure facerecognition performance on frontal facial images takenJ., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the facerecognition grand challenge. [HTML]

Local discriminant wavelet packet coordinates for face recognition
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In Bhagavatula and Savvides (2005), PCA is per- formed in wavelet packet subbands andLOCAL DISCRIMINANT WAVELET PACKET COORDINATES FOR FACERECOGNITION with depth 2. (Bottom) The two-dimensional wavelet packet decomposition of facial image with

Optimal sampling of Gabor features for face recognition
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However, different facial regions have different levels of importance for facerecognition, and Therefore, we randomly selected 21 face subjects (12 male and 9 female) from the training images, which also reflects the corresponding importance in distinguishing the human faces.

Recent advances in visual and infrared face recognition a review
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In verification tasks, the system confirms or rejects the claimed identity of the input face. Additional information such as race, age, gender, and facial expression can be used to enhanceHuman faces look similar in structure with minor differences from person to person.

A trainable system for object detection
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The diagonal wavelets respond strongly to the endpoint of facial features. 2.2.2. Analyzing the People Class.In the case of faces, there are clear patterns within the face, consisting of the eyes, nose and mouth; these pat- terns are common to all the examples.

Face recognition using particle swarm optimization-based selected features
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The ORL database of faces contains a set of face images taken between April 1992 andEach subject has 10 different images taken in various sessions varying the lighting, facial expressions (open/ closed eyes, smiling/ not smiling) and facial details (glasses/ no glasses).

3D shape-based face recognition using automatically registered facial surfaces
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In this work, we have proposed a novel 3D face recogni- tion system based only on theProposed algorithm (PSD) first establishes a dense correspondence between faces.is carried out by computing a discrete approx- imation of a volume between registered facial surfaces.



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