This hands-on guide gives an overview of computer vision and enables engineers to understand the implications and challenges behind mobile platform design choices. Using face-related algorithms as examples, the author surveys and illustrates how design choices and algorithms can be geared towards developing power-saving and efficient applications on resource constrained mobile platforms. Presents algorithms for face detection and recognition Explains applications of facial technologies on mobile devices Includes an overview of other computer vision technologies
The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions. This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systems Provides comprehensive coverage of face detection, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications Contains numerous step-by-step algorithms Describes a broad range of applications from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry.
Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver's license issuance, law enforcement investigations, and physical access control.Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face de
Although the history of computer-aided face recognition stretches back to the 1960s, automatic face recognition remains an unsolved problem and still offers a great challenge to computer-vision and pattern recognition researchers. This handbook is a comprehensive account of face recognition research and technology, written by a group of leading international researchers. Twelve chapters cover all the sub-areas and major components for designing operational face recognition systems. Background, modern techniques, recent results, and challenges and future directions are considered. The book is aimed at practitioners and professionals planning to work in face recognition or wanting to become familiar with the state-of- the-art technology. A comprehensive handbook, by leading research authorities, on the concepts, methods, and algorithms for automated face detection and recognition. Essential reference resource for researchers and professionals in biometric security, computer vision, and video image analysis.
Facial recognition software has improved by leaps and bounds over the past few decades, with error rates decreasing significantly within the past ten years. Though this is true, conditions such as poor lighting, obstructions, and profile-only angles have continued to persist in preventing wholly accurate readings. Face Recognition in Adverse Conditions examines how the field of facial recognition takes these adverse conditions into account when designing more effective applications by discussing facial recognition under real world PIE variations, current applications, and the future of the field of facial recognition research. The work is intended for academics, engineers, and researchers specializing in the field of facial recognition.
This authoritative text/reference presents a comprehensive review of algorithms and techniques for face recognition (FR), with an emphasis on systems that can be reliably used in operational environments. Insights are provided by an international team of pre-eminent experts into the processing of multispectral and hyperspectral face images captured under uncontrolled environments. These discussions cover a variety of imaging sensors ranging from state-of-the-art visible and infrared imaging sensors, to RGB-D and mobile phone image sensors. A range of different biometric modalities are also examined, including face, periocular and iris. This timely volume is a mine of useful information for researchers, practitioners and students involved in image processing, computer vision, biometrics and security.
The purpose of this application is to develop an embedded system application which is able to collect face image and recognize the face by comparing with the database inside the system. Face recognition as a type of biometric methods has the features of non-contact, safety and convenience. It is widely used in human-computer interaction, transaction authentication, security and other fields. Recent years, with the development of mobile internet and embedded computer, it becomes possible to run face recognition on embedded system. This type of application has huge potential in remote payment and personal information security. This application is running on Android operating system which is an operating system based on the Linux kernel, and designed primarily for touchscreen mobile devices such as smartphones and tablet computers. The procedure of face recognition includes face detection, face normalization and recognition. This paper studies these key issues and successfully developed an application with nice recognition rate. The main contents and results are as follows:1) Discusses the face detection method. It used Adaboost algorithm and Haar features to detect human faces.2) Studies image pre-processing methods. Standardize the images so as to minimize the storage space and speed up the computation speed. 3) Summarize a variety of face recognition algorithms especially principle component analysis which is used in this application. Discuss the theoretical foundation of PCA algorithm. 4) Fulfilled all the features from face detection to recognition in Android platform. Using ORL face image database for testing and got a correct identification rate of over 85%. Fully verify the effectiveness of the program. Discuss the results and identification strategies.
Face recognition technologies (FRTs) have many practical security-related purposes, but advocacy groups and individuals have expressed apprehensions about their use. This report highlights the high-level privacy and bias implications of FRT systems. The authors propose a heuristic with two dimensions -- consent status and comparison type -- to help determine a proposed FRT's level of privacy and accuracy. They also identify privacy and bias concerns.
