Stan Z. Li - Handbook of Face Recognition
Here you can read online Stan Z. Li - Handbook of Face Recognition full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. City: London, publisher: Springer London, genre: Children. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:
Romance novel
Science fiction
Adventure
Detective
Science
History
Home and family
Prose
Art
Politics
Computer
Non-fiction
Religion
Business
Children
Humor
Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.
- Book:Handbook of Face Recognition
- Author:
- Publisher:Springer London
- Genre:
- City:London
- Rating:5 / 5
- Favourites:Add to favourites
- Your mark:
Handbook of Face Recognition: summary, description and annotation
We offer to read an annotation, description, summary or preface (depends on what the author of the book "Handbook of Face Recognition" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.
Management Basics in easy steps, 2nd edition offers practical tips, information and common-sense advice based on the authors 40 years hands-on experience of management - now updated to reflect advances in technology and changes in the wider working environment. Whether you are an experienced manager or about to take up your first management job, Management Basics in easy steps, 2nd edition will be of real help to you in the workplace. It is a lively, easy-to-read book, full of tips and simple, practical things that have been put into practice in the real world and shown to work where it matters - in the workplace. Tony Rossiters clear, humorous writing style and comprehensive content make Management Basics in easy steps, 2nd edition a compelling must-read for anyone with a management role. His management tips and advice will show you: How people skills help you put into practice all the technical skills needed by a manager; How to manage your staff, your colleagues, your customers and even your boss; How to organise yourself and make the most effective use of your time; How to focus on the vital 20% of your work that accounts for most of the results; How to win the respect and trust of your team and make it the best; How to select the right person to join your team; The art of effective delegation; How to make effective use of digital tools, online networks and social media; How to cope with change and see it not as a threat but as a great opportunity. This second edition has been revised to include the changes in management practices since the first edition, which was published in 2011, including: The increased importance and use of digital tools, business and performance management software, and social networks (e.g. LinkedIn, Slack, Yammer, Scoro, Twitter, Facebook); Increased focus on diversity and inclusion Implications of new data protection legislation; Less tolerance of unacceptable workplace behaviour such as bullying and sexual harassment; More recognition of the importance of the culture of an organisation; A move away from traditional, command-and-control hierarchies towards more flexible working - working from home, better work/life balance, teamwork, collaboration, matrix structures, trusting and empowering those at the coal-face; A move away from fixed appraisal systems and formal training towards continuous feedback, coaching and personal learning (e-learning, distance learning); More refined recruitment (use of LinkedIn etc) Comes with useful worksheets - a complete guide for easy reference.
Stan Z. Li: author's other books
Who wrote Handbook of Face Recognition? Find out the surname, the name of the author of the book and a list of all author's works by series.
Stan Z. Li
Davies A. Igberaese
SAGE India
G. Edward Evans
Lou Russell
Lisa Haneberg
Handbook of Face Recognition — read online for free the complete book (whole text) full work
Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Handbook of Face Recognition" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.
Light
Font size:
↓
↑
Reset
Interval:
↓
↑
Bookmark:
Make
Stan Z. Li and Anil K. Jain (eds.) Handbook of Face Recognition Second Edition 10.1007/978-0-85729-932-1_1 Springer-Verlag London Limited 2011
1. Introduction
Stan Z. Li 1
(1)
Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
(2)
Michigan State University, East Lansing, MI 48824, USA
Stan Z. Li (Corresponding author)
Email:
Anil K. Jain
Email:
Abstract
This chapter provides an introduction to face recognition research. Main steps of face recognition processing are described. Face detection and recognition problems are explained from a face subspace viewpoint. Technology challenges are identified after that. Typical strategies for solving the problems are suggested.
1.1 Face Recognition
Face recognition is a task that humans perform routinely and effortlessly in our daily lives. Wide availability of powerful and low-cost desktop and embedded computing systems has created an enormous interest in automatic processing of digital images in a variety of applications, including biometric authentication, surveillance, human-computer interaction, and multimedia management. Research and development in automatic face recognition follows naturally.
Face recognition has several advantages over other biometric modalities such as fingerprint and iris: besides being natural and nonintrusive, the most important advantage of face is that it can be captured at a distance and in a covert manner. Among the six biometric attributes considered by Hietmeyer [. Face recognition, as one of the major biometric technologies, has become increasingly important owing to rapid advances in image capture devices (surveillance cameras, camera in mobile phones), availability of huge amounts of face images on the Web, and increased demands for higher security. 
Fig. 1.1
A scenario of using biometric MRTD systems for passport control ( left ), and a comparison of various biometric traits based on MRTD compatibility ( right , from Hietmeyer [] with permission)
The first automated face recognition system was developed by Takeo Kanade in his Ph.D. thesis work [].
Face recognition technology is now significantly advanced since the time when the Eigenface method was proposed. In the constrained situations, for example where lighting, pose, stand-off, facial wear, and facial expression can be controlled, automated face recognition can surpass human recognition performance, especially when the database (gallery) contains a large number of faces. However, automatic face recognition still faces many challenges when face images are acquired under unconstrained environments. In the following sections, we give a brief overview of the face recognition process, analyze technical challenges, propose possible solutions, and describe state-of-the-art performance.
This chapter provides an introduction to face recognition research. Main steps of face recognition processing are described. Face detection and recognition problems are explained from a face subspace viewpoint. Technology challenges are identified and possible strategies for solving some of the problems are suggested.
1.2 Categorization
As a biometric system, a face recognition system operates in either or both of two modes: (1) face verification (or authentication), and (2) face identification (or recognition). Face verification involves a one-to-one match that compares a query face image against an enrollment face image whose identity is being claimed. Person verification for self-serviced immigration clearance using E-passport is one typical application.
Face identification involves one-to-many matching that compares a query face against multiple faces in the enrollment database to associate the identity of the query face to one of those in the database. In some identification applications, one just needs to find the most similar face. In a watchlist check or face identification in surveillance video, the requirement is more than finding most similar faces; a confidence level threshold is specified and all those faces whose similarity score is above the threshold are reported.
The performance of a face recognition system largely depends on a variety of factors such as illumination, facial pose, expression, age span, hair, facial wear, and motion. Based on these factors, face recognition applications may be divided into two broad categories in terms of a users cooperation: (1) cooperative user scenarios and (2) noncooperative user scenarios.
The cooperative case is encountered in applications such as computer login, physical access control, and e-passport, where the user is willing to be cooperative by presenting his/her face in a proper way (for example, in a frontal pose with neutral expression and eyes open) in order to be granted the access or privilege.
In the noncooperative case, which is typical in surveillance applications, the user is unaware of being identified. In terms of distance between the face and the camera, near field face recognition (less than 1 m) for cooperative applications (e.g., access control) is the least difficult problem, whereas far field noncooperative applications (e.g., watchlist identification) in surveillance video is the most challenging.
Applications in-between the above two categories can also be foreseen. For example, in face-based access control at a distance, the user is willing to be cooperative but he is unable to present the face in a favorable condition with respect to the camera. This may present challenges to the system even though such cases are still easier than identifying the identity of the face of a subject who is not cooperative. However, in almost all of the cases, ambient illumination is the foremost challenge for most face recognition applications.
1.3 Processing Workflow
Face recognition is a visual pattern recognition problem, where the face, represented as a three-dimensional object that is subject to varying illumination, pose, expression, and other factors, needs to be identified based on acquired images. While two-dimensional face images are commonly used in most applications, certain applications requiring higher levels of security demand the use of three-dimensional (depth or range) images or optical images beyond the visual spectrum. A face recognition system generally consists of four modules as depicted in Fig. : face localization, normalization, feature extraction, and matching. These modules are explained below. 
Fig. 1.2
Depiction of face recognition processing flow
Face detection segments the face area from the background. In the case of video, the detected faces may need to be tracked across multiple frames using a face tracking component. While face detection provides a coarse estimate of the location and scale of the face, face landmarking localizes facial landmarks (e.g., eyes, nose, mouth, and facial outline). This may be accomplished by a landmarking module or face alignment module.
Face normalization is performed to normalize the face geometrically and photometrically. This is necessary because state-of-the-art recognition methods are expected to recognize face images with varying pose and illumination. The geometrical normalization process transforms the face into a standard frame by face cropping. Warping or morphing may be used for more elaborate geometric normalization. The photometric normalization process normalizes the face based on properties such as illumination and gray scale.
Light
Font size:
↓
↑
Reset
Interval:
↓
↑
Bookmark:
Make
Similar books «Handbook of Face Recognition»
Look at similar books to Handbook of Face Recognition. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.
Davies A. Igberaese
SAGE India
G. Edward Evans
Lou Russell
Lisa Haneberg
Reviews about «Handbook of Face Recognition»
Discussion, reviews of the book Handbook of Face Recognition and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.