face recognition methods applications and technology pdf

Face Recognition Methods Applications And Technology Pdf

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Face recognition, as one of the most successful applications of image analysis, has recently gained significant attention. It is due to availability of feasible technologies, including mobile solutions. Research in automatic face recognition has been conducted since the s, but the problem is still largely unsolved. Last decade has provided significant progress in this area owing to advances in face modelling and analysis techniques.

Face Recognition and its Application

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs and how to get involved. Authors: Divyarajsinh N. Parmar , Brijesh B. CV] for this version. Full-text links: Download: PDF only license.

Facial recognition system

The Journal of Applied Research and Technology JART is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research. JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: Material Science Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors. Computer Science Computer graphics and visualization, programming, human-computer interaction, neural networks, image processing and software engineering.

Face Recognition: Issues, Methods and Alternative Applications

The development of biometric applications, such as facial recognition FR , has recently become important in smart cities. Many scientists and engineers around the world have focused on establishing increasingly robust and accurate algorithms and methods for these types of systems and their applications in everyday life. FR is developing technology with multiple real-time applications. The goal of this paper is to develop a complete FR system using transfer learning in fog computing and cloud computing.

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Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. A Comparative Study of Baseline Algorithms of Face Recognition Abstract: In this paper we present a comparative study of two well-known face recognition algorithms. The contribution of this work is to reveal the robustness of each FR algorithm with respect to various factors, such as variation in pose and low resolution of the images used for recognition. This evaluation is useful for practical applications where the types of the expected images are known.

A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services , works by pinpointing and measuring facial features from a given image. While initially a form of computer application , facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics. Because computerized facial recognition involves the measurement of a human's physiological characteristics facial recognition systems are categorised as biometrics. Although the accuracy of facial recognition systems as a biometric technology is lower than iris recognition and fingerprint recognition , it is widely adopted due to its contactless process. Automated facial recognition was pioneered in the s. Their early facial recognition project was dubbed "man-machine" because the coordinates of the facial features in a photograph had to be established by a human before they could be used by the computer for recognition. On a graphics tablet a human had to pinpoint the coordinates of facial features such as the pupil centers, the inside and outside corner of eyes, and the widows peak in the hairline.

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Biometric Solutions pp Cite as. Face recognition has long been a goal of computer vision, but only in recent years reliable automated face recognition has become a realistic target of biometrics research. New algorithms, and developments spurred by falling costs of cameras and by the increasing availability processing power have led to practical face recognition systems. These systems are increasingly being deployed in a wide range of practical applications, and future improvements promise to spread the use of face recognition further still. In this chapter, we review the field of face recognition, analysing its strengths and weaknesses and describe the applications where the technology is currently being deployed and where it shows future potential. We describe the IBM face recognition system and some of its application domains. Unable to display preview.

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    PDF | Face recognition presents a challenging problem in the field of image Divyarajsinh N Parmar et al,aidshealing.orger Technology & Applications,Vol 4 (1).

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    Over the past few decades, interest in theories and algorithms for face recognition has been growing rapidly.

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