File Name: face detection and recognition theory and practice .zip
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.
In this paper, the algorithm of face recognition technology is made a comprehensive study. Firstly studied the methods of face detection, facial feature of bottom-up approach, template matching method, the method of face appearance, and then focused on color-based face detection algorithm. After studied method on face detection, the region segmentation of the face and the mark of facial feature are described. Finally two methods of face detection are proposed, the first method for the similarity-based approach, through similarity calculation, binary face region after the mark. The second method is based on areas of skin, hair regional approach. It is used to detect the use of color face region approach. In the face region detection is completed later on detected human face of the facial features of the mark.
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. Although systems have been developed for face detection and tracking, reliable face recognition still offers a great challenge to computer vision and pattern recognition researchers. There are several reasons for recent increased interest in face recognition, including rising public concern for security, the need for identity verification in the digital world, face analysis and modelling techniques in multimedia data management and computer entertainment. In this chapter, we have discussed face recognition processing, including major components such as face detection, tracking, alignment and feature extraction, and it points out the technical challenges of building a face recognition system.
English. format. PDF. unavailableOnMobile. Unavailable on the mobile app Face Detection and Recognition: Theory and Practice elaborates on and explains.
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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Face Detection and Recognition Theory and Practice eBookslib · 1 Automated face recognition system 5 · 2 Process flow in face recognition.
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PDF | This book discusses the major approaches, algorithms, and technologies used in automated face detection and recognition. Explaining.Togfulotan1958 20.03.2021 at 11:37
Face Detection and Recognition: Theory and Practice provides students, researchers, and practitioners with a single source for cutting-edge information on the.