Mason, James Eric
Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force
- ISBN 13:
- 9783319804866
- author:
- Mason, James Eric
- format:
- Paperback
- publisher:
- Springer
- language:
- English
- Publication Year:
- 2018
- Pages:
- 260
- Dimensions:
- 23.4 x 15.6 x 1.4 centimetres (0
- Genre:
- Computers, Computer Science, Nonfiction, Nonfiction
- Condition:
- New
- Availability:
- Item usually sent within 20 working days
Description
This book explores how machine learning techniques can be applied to analyze and utilize gait biometrics, a type of behavioral biometric. A comprehensive framework for Ground Reaction Force-based Gait Biometrics Recognition is presented and validated through experiments.
It also delves into the analysis of existing recognition techniques suited for footstep GRF-based person recognition, compares feature extractors, normalizers, and classifiers configurations, and proposes novel data processing techniques specifically designed for gait biometric recognition using Ground Reaction Force. The book provides a detailed theoretical overview of various machine learning techniques leading to two novel approaches developed for this purpose.
Key research challenges and open issues in gait biometrics recognition are discussed, as well as the impact of footwear and stepping speed on footstep GRF-based person recognition. This book bridges existing research gaps and offers a comparison of biometrics systems trained with different footwear conditions.
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