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

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

byIsaac Woungang, Issa Traoré, James Eric Mason

Kobo ebook | February 4, 2016

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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

Title:Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction ForceFormat:Kobo ebookPublished:February 4, 2016Publisher:Springer International PublishingLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319290886

ISBN - 13:9783319290881

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