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.
| ISBN: | 9783319248639 |
| Publication date: | 4th November 2015 |
| Author: | Ajita Rattani, Fabio Roli, Eric Granger |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Hardback |
| Pagination: | 134 pages |
| Series: | Advances in Computer Vision and Pattern Recognition |
| Genres: |
Pattern recognition Digital signal processing (DSP) Electronics engineering Artificial intelligence |
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.
Adaptive Biometric Systems features in the following genres: Pattern recognition, Digital signal processing (DSP), Electronics engineering, Artificial intelligence
Adaptive Biometric Systems is available in Hardback
Adaptive Biometric Systems was written by Ajita Rattani, Fabio Roli, Eric Granger and published by Springer an imprint of Springer International Publishing
Adaptive Biometric Systems has 134 pages
Yes it is part of Advances in Computer Vision and Pattern Recognition series