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Opis

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

Szczegóły książki

Kategoria Książki po angielsku Computing & information technology Computer science Artificial intelligence

• Pełny tytuł: Machine Learning Techniques for Gait Biometric Recognition
• Podtytuł: Using the Ground Reaction Force
• Autor: JAMES ERIC MASON
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 223
• EAN: 9783319804866
• ISBN: 9783319804866
• ID: 19308760
• Wydawca: Springer International Publishing AG
• Waga: 414 g
• Wymiary: 156 × 233 × 20 mm
• Data wydania: 30. March 2018

Ulubione w innej kategorii

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