This 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. Features: presents a thorough
introduction to the concept of adaptive biometric systems; 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.
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