Over the last decade, interest in biometric based identification and verification systems has increased considerably. One application is the use of speech signals, face images or fingerprints in order to supplement security systems based on passwords.Biometric recognition can also be applied to other areas, such as passport control (immigration checkpoints), forensic work (to determine whether a biometric sample belongs to a suspect) and law enforcement applications (e.g. surveillance). While biometric systems based on face images and/or speech signals can be effective, their performance can degrade in the presence of challenging conditions. In face based systems this can be in the form of a change in the illumination direction and/or face pose variations. Multi-modal systems use more than one biometric at the same time, for two main reasons: to achieve better robustness and to increase discrimination power. This book can serve as a useful primer for face and speech processing, as well as information fusion. It reviews relevant backgrounds and reports research aimed at increasing the robustness of single- and multi-modal biometric identity verification systems.
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About the Author
Conrad Sanderson, PhD: Research Scientist at NICTA and adjunct at University of Queensland, Australia. IEEE member. Studied Engineering & Computer Science at Griffith University. Interests include applied and theoretical areas of machine learning, pattern recognition and computer vision, with applications such as automated surveillance.
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4.0 out of 5 stars
Good overview and alternate approaches to biometrics based on speaker and face recognition,
By J Williams (Los Angeles, USA) - See all my reviews
This review is from: Biometric Person Recognition: Face, Speech and Fusion (Paperback)
This book is aimed at engineers, scientists and graduate students. It provides an overview of research and results in the areas of information fusion, speaker and face recognition, with a specific focus on how it applies to biometrics. While it doesn't cover every possible area and not all the developments, it is a good introduction to the main concepts and approaches. In some ways it can be thought of as a time saver (instead of reading sets of disparate articles), which additionally provides interesting research results.
Amongst other things, the author shows that automatic face recognition can be performed quite successfully even if the topology of the face is lost. This is at first counter intuitive, but provides advantages in terms of robustness to face alignment problems, in addition to reducing pose and illumination issues. The author then expands the idea by showing that pose changes can be handled by transformations of statistical model parameters rather than image transformations. Even though more details and more elaborate explanations would have been helpful to people less versed in the area, this book is a useful addition to a library on biometrics.
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