Machine Learning Techniques for Gait Biometric Recognition - Using the Ground Reaction Force (Hardcover, 1st ed. 2016)

This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book * introduces novel machine-learning-based temporal normalization techniques * bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition * provides detailed discussions of key research challenges and open research issues in gait biometrics recognition* compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	February 2016
First published:	2016
Authors:	James Eric Mason • Issa Traore • Isaac Woungang
Dimensions:	235 x 155 x 16mm (L x W x T)
Format:	Hardcover
Pages:	223
Edition:	1st ed. 2016
ISBN-13:	978-3-319-29086-7
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Professional & Technical > Civil engineering, surveying & building > Building construction & materials > Security & fire alarm systems Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-319-29086-X
Barcode:	9783319290867

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