1.

Record Nr.

UNINA9910298963303321

Titolo

Adaptive Biometric Systems : Recent Advances and Challenges / / edited by Ajita Rattani, Fabio Roli, Eric Granger

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015

ISBN

3-319-24865-0

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (141 p.)

Collana

Advances in Computer Vision and Pattern Recognition, , 2191-6586

Disciplina

006.4

Soggetti

Biometrics (Biology)

Pattern recognition

Signal processing

Image processing

Speech processing systems

Artificial intelligence

Biometrics

Pattern Recognition

Signal, Image and Speech Processing

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Sommario/riassunto

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.