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
Proposes a score-level fusion scheme for an adaptive multimodal biometric system
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
students of computer engineering will also appreciate the coverage of intelligent and adaptive schemes for cutting-edge pattern recognition and signal processing in changing environments.
