Behavioral Biometrics for Human Identification: Intelligent Applications (pdf) by Liang Wang & Xin Ceng
The science of biometrics has advanced considerably over the past decade. It has now reached a position where there is general acceptance that people are unique by biometrics, and can be identified by them. Issues that remain for general resolution include the more pragmatic aspects, such as implementation issues (not just how the systems can operate, but also how people can interact with them) and analysis of results and performance. Given this acceptance, it is then correct that the research agenda should develop a wider remit.
That this is already happening is reflected in the diversity of new conference agendas on biometrics and of the emergence of new texts, such as this one. That makes this text very timely indeed. It is also very timely for its novelty: this is the first text on behavioural biometrics for human identification.
That a person can be identified by behavioural activities is entirely consistent with the notion of biometrics. The techniques for automated writer identification have a long history; gait is an inherently behavioural biometric wherein identity is reflected by the nature of variation of human body pose. Having been a long-time researcher in biometrics, I have seen the research path from concept to implementation many times. There is an ideas phase, where the notions of identity verification/recognition are first exposed. When this has been achieved, there is an issue of performance evaluation, and later on standardised analysis. Then, there is the need for real-time implementation in a system convenient for use and deployment. Finally, there is the need to convince the general public not just that these systems do indeed ascertain identity, but also that they work and are generally acceptable. This is the first text on behavioural biometrics, and is at the nascent stage of this new technology.
It is not surprising that some of oldest behavioural biometrics are to be found in extended and contemporary form within this volume. There are works here in describing text-independent writer identification, and keystroke input which is of increasing importance given the prevalence of web technologies. Given its importance as a behavioural biometric, it is no surprise that there are works here which survey the recent advances in gait, and which extend identification approaches by using bilinear models, and by gait feature fusion. An extension to these is to recognise people by their style of performing particular actions.
There is of course a wider remit in behaviour than there is in biometrics, for behaviour can concern not only personal variation, but also their interaction with a computer system or another device. In this we are found to be individual by the way we behave, as well as by physical characteristic. That is reflected here in that there are approaches based on using biosignals (electroencephalogram and electrocardiogram data), on a user’s mouse dynamics, on a user’s gaze when viewing familiar and unfamiliar scenes, and on a user’s visual attention. Taking the approaches beyond more conventional biometrics, it is even show how recognition can be achieved based on a user’s game-playing strategy.
The advance of recognition technique is usually paralleled by advance in the enabling technologies, and by advance in evaluation and that is to be found here. This new text contains works which define the remit by it taxonomy, which consider security evaluation to increase confidence, and on techniques and standard for performance evaluation. The technology concerns technique, here by Gabor wavelets, and by sensor technology, here by infrared. There is natural concern of security and by deployment of fusion to enhance recognition capability. In these respects, this text approaches major areas of interest in these new approaches.
The editorial team has assembled an impressive set of contributors and an impressive variety of contributions. I believe they encompass the majority of areas consistent with a new technology, covering basis, implementation, and evaluation. I look forward to analysing and discussing the content of this first text on behavioural biometrics, to the research that it contains, and that which it inspires.
Mark S. Nixon / University of Southampton February 2009
Table of Contents
Behavioral Biometrics for Human Identification
Taxonomy of Behavioural Biometrics / Roman V. Yampolskiy, University of Louisville, USA Venn Govindaraju, University at Buffalo, USA
Security Evaluation of Behavioral Biometric Systems / Olaf Henniger, Fraunhofer Institute for Secure Information Technology, Germany
Performance Evaluation of Behavioral Biometric Systems /
F. Cherifi, University of Caen, France
B. Hemery, University of Caen, France R. Giot, University of Caen, France
M. Pasquet, University of Caen, France
C. Rosenherger, University of Caen, France
Individual Identification from Video Based on “Behavioural Biometrics”
Y. Pratheepan, University of Ulster, UK J.V. Condell, University of Ulster, UK G. Prasad, University of Ulster, UK
Behavioral Biometrics: A Biosignal Based Approach
Kenneth Revett, University of Westminster, UK
Gabor Wavelets in Behavioral Biometrics
M. AshraJ’ul Amin, City University of Hong Kong, Hong Kong Hong Yan, City University of Hong Kong, Hong Kong
Gait Recognition and Analysis
Shiqi Yu, Chinese Academy of Sciences/The Chinese University of Hong Kong, China Liang Wang, The University of Melbourne, Australia
Multilinear Modeling for Robust Identity Recognition from Gait
Fa bio Cuzzolin, Oxford Brookes University, UK
Gait Feature Fusion using Factorial HMM
Jim in Liang, Xidian University, China Changhong Chen, Xidian University, China Heng Zhao, Xidian University, China Haihong Hu, Xidian University, China Jie Tian, Xidian University, China
Mouse Dynamics Biometric Technology
Ahmed Awad E. Ahmed, University of Victoria, Canada Issa Traore, University of Victoria, Canada
Activity and Individual Human Recognition in Infrared Imagery
Bir Bhanu, University of California – Riverside, USA Ju Han, University of California – Riverside, USA
Gaze Based Personal Identification
Clinton Fookes, Queensland University of Technology, Australia Anthony Maeder, CSIROICT Centre, Australia Sridha Sridharan, Queensland University of Technology, Australia George Mamie, Queensland University of Technology, Australia
Speaker Verification and Identification
Minho Jin, Korea Advanced Institute of Science and Technology, Republic of Korea Chang D. Yoo, Korea Advanced Institute of Science and Technology, Republic of Korea
Visual Attention for Behavioral Biometric Systems
Concetto Spampinato, University of Catania, Italy
Statistical Features for Text-Independent Writer Identification
Zhenan Sun, NLPR, CAS, China Bangyu Li, NLPR, CAS, China Tieniu Tan, NLPR, CAS, China
Keystroke Biometric Identification and Authentication on Long-Text Input
Charles C. Tappert, Pace University, USA Mary Villani, Pace University, USA Sung-Hyuk Cha, Pace University, USA
Secure Dynamic Signature-Crypto Key Computation
Andrew Teoh В eng Jin, Yonsei University, Korea Yip Wai Kuan, Multimedia University, Malaysia
Game Playing Tactic as a Behavioral Biometric for Human Identification
Roman V Yampolskiy, University of Louisville, USA Venn Govindaraju, University at Buffalo, USA
Multimodal Biometrics Fusion for Human Recognition in Video
Xiaoli Zhou, University of California – Riverside, USA Bir Bhanu, University of California – Riverside, USA
Compilation of References
About the Contributors
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