Издательство World Scientific, 2007, -453 pp.Computer Vision and Computer Graphics can be thought of as opposite sides of the same coin. In computer graphics we start, for example, with a three-dimensional model of a face, and we attempt to render or project this model onto a two-dimensional surface to create an image of the face. In computer vision we attempt to do the opposite — we start with a two-dimensional image of the face and we try to generate a computer model from a sequence of one or more such images. However, the two sides of the coin are by no means equal as far as the amount of research and development lavished upon them; computer graphics is a very advanced and developed field, whereas computer vision is still relatively in its infancy. This is largely because developments in computer graphics have been driven forwards by the multi-billion dollar markets for computer aided design, computer games, and the movie and advertising industry. It therefore makes a great deal of sense to try and exploit this powerful relationship between the two fields so that computer vision can benefit from the wealth of powerful techniques already developed for computer graphics.
In this book we apply this thinking to a field which whilst not exactly a sub-discipline of computer vision has a very great deal in common with it. This field is Biometrics where we attempt to generate computer models of the physical and behavioural characteristics of human beings with a view to reliable personal identification. It is not completely a sub-discipline of computer vision because the human characteristics of interest are not restricted to visual images, but also include other human phenomena such as odour, DNA, speech, and indeed anything at all which might help to uniquely identify the individual.
Although biometrics is at least as old as computer vision itself, research and development in this field has proceeded largely independently of computer graphics. We strongly believe that this has been a mistake in the past and we will attempt to redress this balance by developing the other side of the biometrics coin, namely Biometric Synthesis — rendering biometric phenomena from their corresponding computer models. For example, we could generate a synthetic face from its corresponding computer model. Such a model could include muscular dynamics to model the full gamut of human emotions conveyed by facial expressions.
We firmly believe that this will be a very fertile area of future research and development with many spin-offs. For example, much work has already been done on the information theory associated with computer graphics; just think of image and video compression — we can now fit a complete high quality video compression. We should be able to exploit this valuable research to gain a much better understanding of the information theoretic aspects of biometrics which are not very well understood at present. This is just one example of how this powerful dual relationship between computer graphics and computer vision might be exploited.
This book is a collection of carefully selected chapters presenting the fundamental theory and practice of various aspects of biometric data processing in the context of pattern recognition. The traditional task of biometric technologies — human identification by analysis of biometric data is extended to include the new discipline, Biometric Synthesis— the generation of artificial biometric data from computer models of target biometrics. Some of new ideas were first presented at the International Workshop on Biometric Technologies: Modeling and Simulation held in June 2004 in Calgary, Canada, and which was hosted by the research laboratory of the same name, from which the workshop took its title, Biometric Technologies: Modeling and Simulation at the University of Calgary.
The book is primarily intended for computer science, electrical engineering, and computer engineering students, and researchers and practitioners in these fields. However, individuals in other areas who are interested in these and related subjects will find it a most comprehensive source of relevant information.Part 1: Synthesis in Biometrics
Introduction to Synthesis in Biometrics
Signature Analysis, Verification and Synthesis in Pervasive Environments
Local B-Spline Multiresolution with Example in Iris Synthesis and Volumetric Rendering
Computational Geometry and Image Processing in Biometrics: On the Path to Convergence
Part 2: Analysis in Biometrics
A Statistical Model for Biometric Verification
Composite Systems for Handwritten Signature Recognition
Force Field Feature Extraction for Ear Biometrics
Nontensor-Product-Wavelet-Based Facial Feature Representation
Palmprint Identification by Fused Wavelet Characteristics
Behavioral Biometrics for Online Computer User Monitoring
Part 3: Biometric Systems and Applications
Large-Scale Biometric Identification: Challenges and Solutions
Evolutionary Algorithms: Basic Concepts and Applications in Biometrics
Some Concerns on the Measurement for Biometric Analysis and Applications
Issues Involving the Human Biometric Sensor Interface
Fundamentals of Biometric-Based Training System Design
