Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Softcover reprint of the original 1st ed. 2016
Book Details
Format
Paperback / Softback
ISBN-10
3319804863
ISBN-13
9783319804866
Edition
Softcover reprint of the original 1st ed. 2016
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Mar 30th, 2018
Print length
223 Pages
Weight
414 grams
Dimensions
15.60 x 23.30 x 2.00 cms
Ksh 8,100.00
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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
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