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    Face Recognition

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    last thirty years or so, face recognition is an active research area in computer vision and one of the most successful applications of image analysis and understanding. Different algorithms have been proposed by researchers for solving this problem and many of them are considered as the state of the art. Nowadays, the face recognition problem is not only important in the research area, but it is vital in the commercial applications. A general statement of the face recognition problem can be formulated

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    have been several face recognition methods based on 3D information were introduced [11-13]. Cartoux et al. [ ] introduced a first contributions to this field, which were mainly based on the extraction of a curvature representation of the face from range images and features were used to match the different faces. Xu et al. [48] proposed automatic 3D face recognition by combining global geometric features with local shape variation and resulted 96.1 percent and 72.6 percent recognition rates when using

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    2.0 Literature Review Face detection is a computer technology that will identify human faces in arbitrary images and human faces basically have the same basic configure appearance such as two eyes above a nose and mouth. After the computers have successfully on detecting the faces, there are more researches have done in face processing include emotion recognition. 2.1 Face Acquisition In this process, user’s faces are acquired in order to extract out the facial features from cluttered background

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    Aatumetoc feci ricugnotoun hes elweys biin e mejur fucas uf risierch fur e fiw dicedis, biceasi uf namiruas prectocel epplocetouns whiri hamen odintofocetoun os niidid. Cumperid tu uthir mithuds uf odintofocetoun (sach es fongirpronts, vuoci, fuutpront, ur ritone), feci ricugnotoun hes thi edventegi uf ots nun-onvesovi end asir froindly netari. Feci omegis cen bi ceptarid frum e dostenci wothuat ontirectong woth thi pirsun, whoch os pertocalerly binifocoel fur sicaroty end sarviollenci parpusis.

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    The Importance of the Eyes of a Person's Face in Face Recognition Abstract; The aim of this experiment is to find out if participants can recognise the faces of well known celebrities if the celebrities’ eyes are blacked out and if the eyes of a person’s face are a major factor of face recognition. I predict that the participants will find it easier to recognise the celebrities’ faces in the condition where the eyes are not blacked out more than when the eyes are blacked out. I used

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    Biometrics is a preset method to recognize a person based on a physiological or behavioral attribute. The present features are face recognition, fingerprints, handwriting, hand geometry, iris, vein, voice and retinal scan. In the early years of the 21st century, we find ourselves persistently moving further away from the stipulation of physical human interface playing a major part of basic everyday tasks. Striding ever closer to an programmed society, we interact more habitually with mechanical

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    Face Recognition System

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    A face recognition system aims to determine the identity of a face image with the assistance of a stored database of faces labeled with people’s identities. It is widely considered as one of the most promising biometric techniques, and has attracted much attention in the area of pattern recognition and machine learning. Numerous methods have been proposed in the last decades and they are briefly summarized in surveys of this area [1-3]. These face recognition algorithms generally consist of two steps

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    Occlusion the performance of the face recognition algorithms under occlusion is in general poor. The face may be occluded by other objects in the scene or by sunglasses or other things. Occlusion may be unintentional or intentional. Under some conditions subjects may be motivated to thwart recognition efforts by covering portions of their face. Since in many situations, the goal is to recognize none or even un-cooperating subjects. Time delay Faces change over time. There are changes in hair style

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    According to Shuicheng Yan et al., Misalignment-Robust Face Recognition [3]. Subspace learning techniques for face recognition have been widely studied in the past three decades. In this paper, they study the problem of general subspace-based face recognition under the scheme with spatial misalignments and/or image occlusion. For a given subspace obtained from training data in a supervised, unsupervised, or semi-supervised manner, the implant of a new datum and its underlying spatial misalignments

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    similarity recognition in images of family faces. However, it is appropriate to review research on face recognition, as many of the issues encountered in our problem are similar to those encountered in related problems. Face recognition systems has been carried out in two distinct paradigms. In the first paradigm researchers first extract facial features such as the eyes, nose, etc., then they utilize clustering/classification algorithms to recognition. The second paradigm treats the complete face image

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    Ongoing Challenges Automatic Face Recognition

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    Theoretical difficulties of Automatic Face Recognition Extensive research has been dedicated to the development of computer algorithms, the advancements in automatic face recognition have led to the development of systems that work at high performance rates in a controlled setting. Although computer AFR systems need not necessarily imitate human face recognition processes, humans often compete with the ability of computer algorithms when it comes to recognizing familiar faces even in highly degraded conditions

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    Improve ATM Security by Face Recognition

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    Abstract- In this paper the method face Recognition is using to access Automated teller machines (ATMs). ATMs are used to do banking function like checking balance withdraw money, changing pin numbers etc. The ATM cards and pin numbers are used for security purpose. But this system is using SIM card in place of ATM cards. In order to improve security the system first authenticate the person if he/she is recognized then it will ask the password of the account. This system used Spartan 3 FPGA board

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    Face Recognition Essay

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    ABSTRACT: Face recognition has now become one of the interesting field of research and has received a substantial attention of researchers from all over the world. Face recognition techniques has been widely used in the field of image analysis, image processing, etc. One of the face recognition techniques is used to develop a face recognition system to detect a human face in an image. In face recognition system a digital image with a human face is given as an input which extracts the significant

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    The face has a significant role in social interaction, conveying the identity, expressing emotions and gender recognition etc. The ability of humans in recognizing a face is noteworthy as faces contains important information which helps to differentiate them from one another, therefore humans are able to recognize a large number of faces which they have learned during their life and recognize well-known faces at a quick look even after several years. Face recognition can be defined as the process

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    Face recognition can be defined as the process of scanning a person’s face, then matching that face image with a collection of database i.e. known face images. A human face has lot of rich information however considering the whole information can be less efficient and time consuming. Therefore an efficient system can be made only if we consider the most significant information and discard the rest. Face recognition or identification is a challenging task which not only undergoes from the challenges

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    time biometrics was just beginning to come to the surface. Nowadays systems enabled with fingerprinting security, voice activation, or face recognition have come a long way and are close to fool proof. Biometrics have come even as far to be used at the Super Bowl or other huge sporting events. Cameras have been designed to monitor crowds and be able to take faces and run them through national criminal databases to see if any matches occur. Biometrics is the security of today and tomorrow. In this

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    Biometrics

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    has taken on a whole new definition. Biometrics is an amazing new topic referring to “the emerging field of technology devoted to the identification of individuals using biological traits, based on retinal or iris scanning, fingerprints, or face recognition”. Biometrics has already begun using applications that range from attendance tracking with a time clock to security checkpoints with a large volume of people. The growing field of biometrics has really been put on the map by two things, the

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    Biometrics

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    geometry), iris recognition, face recognition, and fingerprint recognition. Hand geometry can be used in two different ways either using the whole hand for comparison or just using two fingers to identify you. Hand geometry is basically self-explanatory. The device scans either the whole hand or just two fingers of the hand and recognizes hand shape, line in the hands, and other characteristics that are specific to the person’s hand. Another widely used biometric process is iris recognition. How iris

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    2 Face recognition Automatic face recognition is the task of recognizing people from their facial images. There are various challenges that influence automatic face recognition systems, like facial expressions, unlike illumination conditions, partial occlusions of the face, non-frontal pose and low image resolution. Before the person shown in an image could be identified, the face has to be detected. Since we want to examine face recognition, rather than face detection, we use the hand-labelled eye

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    the skin of the face. They are the way of communication in humans which convey many things non- verbally. During the past years face recognition has received significant attention as one of the most important applications of image understanding and analysis. All these factors influence face recognition process. The main stages for face recognition include face detection, feature representation and classifications. Researchers have described distinct approaches for face recognition. In this work we

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