face recognition IEEE PAPER , IEEE PROJECT
Face recognition using eigenfaces
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We present an approach to the detection and identification of human faces and describe a working, near-real-time face recognition system which tracks a subjects head and then recognizes the person by comparing characteristics of the face to those of known
From few to many: Illumination cone models for face recognition under variable lighting and pose
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ABSTRACT We present a generative appearance-based method for recognizing human faces under variation in lighting and viewpoint. Our method exploits the fact that the set of images of an object in fixed pose, but under all possible illumination
Face recognition : A convolutional neural-network approach
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Faces represent complex multidimensional mean-ingful visual stimuli and developing a computational model for face recognition is difficult. We present a hybrid neural-network solution which compares favorably with other methods. The system combines local image
Face recognition : The problem of compensating for changes in illumination direction
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ABSTRACT b Abstract /b A face recognition system must recognize a face from a novel image despite the variations between images of the same face . A common approach to overcoming image variations because of changes in the illumination conditions is to use
Face recognition using the nearest feature line method
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In this paper, we propose a novel classification method, called the nearest feature line (NFL), for face recognition . Any two feature points of the same class (person) are generalized by the feature line (FL) passing through the two points. The derived FL can
Face recognition using kernel direct discriminant analysis algorithms
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Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition (FR) systems. It is well known that the distribution of face images, under a perceivable variation in viewpoint
Face recognition by humans: Nineteen results all computer vision researchers should know about
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A key goal of computer vision researchers is to create automated face recognition systems that can equal, and eventually surpass, human performance. To this end, it is imperative that computational researchers know of the key findings from experimental studies of face
Face recognition with radial basis function (RBF) neural networks
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A general and efficient design approach using a radial basis function (RBF) neural classifier to cope with small training sets of high dimension, which is a problem frequently encountered in face recognition , is presented in this paper. In order to avoid overfitting and
Gabor-based kernel PCA with fractional power polynomial models for face recognition
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ABSTRACT b Abstract /b This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition . Gabor
Discriminant waveletfaces and nearest feature classifiers for face recognition
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Abstractit Feature extraction , it discriminant analysis, and it classification ruleare three crucial issues for face recognition . This paper presents hybrid approaches to handle three issues together. For feature
Beyond eigenfaces: Probabilistic matching for face recognition
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We propose a technique for direct visual matching for face recognition and database search, using a probabilistic measure of similarity which is based on a Bayesian analysis of image differences. Specifically we model two mutually exclusive classes of variation between facial
Learning a spatially smooth subspace for face recognition
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Subspace learning based face recognition methods have attracted considerable interests in recently years, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Locality Preserving Projection (LPP), Neighborhood Preserving Embedding (NPE)
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition
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This paper introduces a novel Gabor-Fisher Classifier (GFC) for face recognition . The GFC method, which is robust to changes in illumination and facial expression, applies the Enhanced Fisher linear discriminant Model (EFM) to an augmented Gabor feature vector
High-speed face recognition based on discrete cosine transform and RBF neural networks
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In this paper, an efficient method for high-speed face recognition based on the discrete cosine transform (DCT), the Fishers linear discriminant (FLD) and radial basis function (RBF) neural networks is presented. First, the dimensionality of the original face image is
Effective representation using ICA for face recognition robust to local distortion and partial occlusion
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The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and ACE and gesture recognition are effortless aspects of interaction among humans, but human- computer interaction remains based upon signals and behaviors which are not natural for us. Although keyboard and mouse are undeniable improvements over tabular switch and In this paper we investigate the performance of a technique for face recognition based on the computation of 25 local autocorrelation coefficients. We use a large database of 11,600 frontal facial images of 116 persons
A survey of approaches to three-dimensional face recognition
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The vast majority of face recognition research has focused on the use of two-dimensional intensity images, and is covered in existing survey papers. This survey focuses on face recognition using three-dimensional data, either alone or in combination with two
GA-fisher: a new LDA-based face recognition algorithm with selection of principal components
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This paper addresses the dimension reduction problem in Fisherface for face recognition . When the number of training samples is less than the image dimension (total number of pixels), the within-class scatter matrix (Sw) in Linear Discriminant Analysis (LDA) is singular In this paper, we propose a novel line feature-based face recognition algorithm. A face is represented by the Face -ARG model, where all the geometric quantities and the structural information are encoded in an Attributed Relational Graph (ARG) structure, then the partial
Face recognition is a method of identifying or verifying the identity of an individual using their face. Face recognition systems can be used to identify people in photos, video, or in real-time.
Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues
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Facial recognition is a key enabling component for emerging Internet of Things (IoT) services such as smart homes or responsive offices. Through the use of deep neural networks, facial recognition has achieved excellent performance. However, this is only
SIGNIFICANCE OF SPECTRAL CURVE IN FACE RECOGNITION
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In this paper, we present the introduction and significance of spectral signature and recognition of skin from hyperspectral face imagery for Face Recognition (FR). In the acquisition step, hyperspectral cameras are used to capture multispectral or hyperspectral
A Review on Different Face Recognition Techniques
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Face recognition has been a quickly developing, testing and intriguing region progressively applications. An extensive number of face recognition calculations have been produced in a decade ago. In this paper an endeavor is made to survey an extensive variety of techniques
Photo Sleuth: Combining Human Expertise and Face Recognition to Identify Historical Portraits
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Identifying people in historical photographs is important for preserving material culture, correcting the historical record, and creating economic value, but it is also a complex and challenging task. In this paper, we focus on identifying portraits of soldiers who participated
A COMPREHENSIVE EXPERIMENTAL COMPARISON OF THE AGGREGATION TECHNIQUES FOR FACE RECOGNITION
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In face recognition , one of the most important problems to tackle is a large amount of data and the redundancy of information contained in facial images. There are numerous approaches attempting to reduce this redundancy. One of them is information aggregation
Multimodal Face and Iris Recognition with Adaptive Score Normalization using Several Comparative Methods
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Objectives: To combine several biometric methods used for face and iris simultaneous recognition of an individual in order to enhance the performance. Methods/Analysis: For every methodology, four approaches are used for features extraction: discrete wavelet
Face Recognition Method Based on Improved Gabor Wavelet Transform Algorithm.
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A face recognition method was proposed based on the improved Gabor wavelet transform algorithm. Firstly, the optimized SSR algorithm was used to carry out the preprocessing on face images. Then the Gabor wavelet transform and the discrete cosine transform (DCT) are
Face Recognition Using HOG and Different Classification Techniques
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Face recognition based unimodal biometric system is developed in this work. The face features are extracted by Histograms of Oriented Gradients (HOG). For person identification of KVKRG face database several techniques were used. In this experiment total, 500 images
NEW ALGORITHM FOR FACE RECOGNITION SYSTEM FOR ENHANCED FEATURE EXTRACTION
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Now a days biometric is a currant topic for the research community. Biometric is used for security purpose for its real time applications. Face recognition is one of the challenging issues in biometrics. These issues in our mind, we are focusing on the face recognition
IoT based Real Time Face Recognition Door Lock System using Neural Network
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Face recognition is one of the most popular and challenging topics in the fields of pattern recognition and computer vision. In this system, Raspberry Pi is used for face recognition . Histogram of Oriented Gradients HOG, Principal Component Analysis PCA and Back
PPCU Sam: Open-source face recognition framework
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Abstract Machine learning has become ubiquitous in our daily lives as technology leaders have started to enhance the user experience with personalized content and adaptive products. Successful enterprises possess resources of data and compute power multiple
Face Recognition using Content Based Image Retrieval for Intelligent Security
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This paper try to construct an intelligent security system based on face recognition . The data used in this research are frontal face images and without obstacles, and facial images with obstacles. In this research, we used Content Based Image Retrieval or CBIR method
An Elementary Study on Various Techniques Involved in Face Recognition Systems: A Review
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Face recognition has now become one of the interesting fields of research and has received a substantial attention of researchers from all over the world. Face recognition techniques has been mostly used in the discipline of image analysis, image processing, etc. One of the
Application of Face Recognition and Location-Based System for Locating Culprit in the Philippines
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Abstract The Philippine National Police (PNP) keep pace on the current developments in IT to enhance their administrations in locating the culprits [10]. However, a timely identification of culprits by the police force is critical to the wellbeing and security of offices and overall
Calculation of the Rate of Taking Lessons Based on Face Recognition and Head Pose Estimation
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Classroom is a place for students to acquire knowledge. However, students attention is easily distracted by various multimedia devices, resulting in the low raise-head rate. In order to create a sound learning atmosphere in the future, it is particularly important to study the
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