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Machine Learning Techniques for Gait Biometric Recognition

Using the Ground Reaction Force

Language EnglishEnglish
Book Hardback
Book Machine Learning Techniques for Gait Biometric Recognition James Eric Mason
Libristo code: 02876432
Publishers Springer International Publishing AG, February 2016
This book focuses on how machine learning techniques can be used to analyze and make use of one part... Full description
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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.

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About the book

Full name Machine Learning Techniques for Gait Biometric Recognition
Author James Eric Mason, Issa Traore, Isaac Woungang
Language English
Binding Book - Hardback
Date of issue 2016
Number of pages 223
EAN 9783319290867
ISBN 331929086X
Libristo code 02876432
Publishers Springer International Publishing AG
Weight 5148
Dimensions 155 x 235 x 20

Categories

Technology, Engineering, Agriculture > Civil engineering, surveying & building > Building construction & materials > Security & fire alarm systems
Technology, Engineering, Agriculture > Other technologies & applied sciences > Applied optics > Imaging systems & technology
Computing & Information Technology > Computer science > Artificial intelligence > Machine learning
Computing & Information Technology > Computer science > Artificial intelligence > Pattern recognition
Computing & Information Technology > Computer science > Artificial intelligence > Computer vision
Technology, Engineering, Agriculture > Technology: general issues > Engineering: general
Technology, Engineering, Agriculture > Electronics & communications engineering > Electronics engineering
Computing & Information Technology > Computer science > Signal processing
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