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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force

Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force

Mason, James Eric
Woungang, Isaac
Traoré, Issa

Paperback

Technology & EngineeringGeneral Computers

ISBN10: 3319804863
ISBN13: 9783319804866
Publisher: Springer
Published: Mar 30 2018
Pages: 223
Weight: 0.81
Height: 0.55 Width: 6.14 Depth: 9.21
Language: English
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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