Machine Learning Techniques for Gait Biometric Recognition
Springer International Publishing (Verlag)
978-3-319-29086-7 (ISBN)
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
James Eric Mason obtained his BSEng and MASc from the University of Victoria, Canada, in 2009 and 2014, respectively. During his Master's program, under the supervision of Dr. Issa Traore, his research focused primarily on biometric security solutions with a particular emphasis on the gait biometric. In 2014 he completed his thesis titled Examining the impact of Normalization and Footwear on Gait Biometrics Recognition using the Ground Reaction Force, which served as an inspiration for the work presented in this book. His research interests include biometric security, machine learning, software engineering, web development, and weather/climate sciences. Since 2011, he has been working with the software startup Referral SaaSquatch as a full stack software developer. Issa Traore obtained a PhD in Software Engineering in 1998 from Institute Nationale Polytechnique (INPT)-LAAS/CNRS, Toulouse, France. He has been with the faculty of the Department of Electrical and Computer Engineering of the University of Victoria since 1999. He is currently a Full Professor and the Coordinator of the Information Security and object Technology (ISOT) Lab at the University of Victoria. His research interests include biometrics technologies, computer intrusion detection, network forensics, software security, and software quality engineering. He is currently serving as Associate Editor for the International Journal of Communication Systems (IJCS) and the International Journal of Communication Networks and Distributed Systems (IJCNDS). Dr. Traore is also a co-founder and Chief Scientist of Plurilock Security Solutions Inc., a network security company which provides innovative authentication technologies, and is one of the pioneers in bringing behavioral biometric authentication products to the market.
Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion.
Erscheinungsdatum | 08.10.2016 |
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Zusatzinfo | XXXIV, 223 p. 76 illus., 3 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Technik ► Elektrotechnik / Energietechnik |
Schlagworte | Behavioral Biometrics • biometrics • Biometrics Recognition framework • Engineering • Footstep GRF-based person recognition • GRF Recognition • Ground Reaction Force (GRF)-based Gait • machine learning • Security Science and Technology • Signal, Image and Speech Processing |
ISBN-10 | 3-319-29086-X / 331929086X |
ISBN-13 | 978-3-319-29086-7 / 9783319290867 |
Zustand | Neuware |
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