Adaptive Biometric Systems: Recent Advances and Challenges (Advances in Computer Vision and Pattern Recognition) - Softcover

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Dr. Ajita Rattani is a post-doctoral fellow in the Integrated Pattern Recognition and Biometrics (i-PRoBe) lab at Michigan State University, East Lansing, MI, USA. Dr. Fabio Roli is a professor of computer engineering and the Director of the Pattern Recognition and Applications (PRA) lab at the University of Cagliari, Italy. Dr. Eric Granger is a professor in the Department of Automated Manufacturing Engineering and the Director of the Laboratory for Imagery, Vision and Artificial Intelligence at the École de technologie supérieure (ÉTS), Montréal, QC, Canada.

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This timely and interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system.

Topics and features:

• Presents a thorough introduction to the concept of adaptive biometric systems, detailing their taxonomy, levels of adaptation, and open issues and challenges
  
• Reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data
  
• Describes a novel semi-supervised training strategy known as fusion-based co-training
  
• Examines the characterization and recognition of human gestures in videos
  
• Discusses a selection of learning techniques that can be applied to build an adaptive biometric system
  
• Investigates procedures for handling temporal variance in facial biometrics due to aging

This comprehensive text/reference will be of great interest to researchers and practitioners engaged in systems science, information security or biometrics. Postgraduate and final-year undergraduate