How can one expect a biometric system that relies on a single enrolment sample to cope with all the variability possibly encountered during the operational phase? To maintain good performance, one way is to combine multiple biometric traits. This approach which is known as multimodal biometrics can be shown theoretically that this approach leads to improved recognition accuracy. This lecture will explore some aspects of multmodal biometric adaptation, ranging from the use of quality measures, user-specific statistics and cohort information to the new exciting development of template-update and adaptive threshold/score normalization techniques.
The goal of the lecture is to show how the above problems can be solved using machine learning techniques as fundamental building blocks. For instance, it will be shown how a clustering algorithm can be combined with a generative/discriminative classifier to form a mixture of linear classifiers that results in the state-of-the-art classifier for quality-based fusion. Another example is how the cohort information can be modelled first by regression and then solved as a classification problem.
Norman Poh is a Lecturer in Computational Intelligence, Department of Computer Science, University of Surrey. He received the Ph.D. degree in computer science in 2006 from the Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland. Prior to this appointment, he was a Research Fellow with the Centre for Vision, Speech, and Signal Processing (CVSSP), University of Surrey, Guildford, Surrey, UK and a research assistant at IDIAP research institute, Swtizerland. His research interests focus on developing and applying pattern recognition theories to biometrics, information fusion, and healthcare informatics. In these areas, he has authored more than 100 peer-reviewed publications.
(longer biography-- if needed) He recieved two personal Fellowships from the Swiss National Science Foundation (Young Prospective and Advanced Researcher grants) and authored five best paper awards (AVBPA'05, ICB'09, HSI 2010, ICPR 2010 and Pattern Recognition Journal 2006). He won the Researcher of the Year 2011 Award, University of Surrey. His project Exo-brain won several prizes in the ICC2013.
He is an Associate Editor of the IET Biometrics Journal, an IEEE Certified Biometrics Professional and trainer, a member of IEEE and IAPR, and a member of the Education Committee of the IEEE Biometric Council. He initiated and maintain Biometrics School (Winter editions): www.biometricschool.org.