Mobile Biometrics
Published on 30. September 2017
Book
Hardback
488 pages
978-1-78561-095-0 (ISBN)
Description
Mobile biometrics - the use of physical and/or behavioral characteristics of humans to allow their recognition by mobile/smart phones - aims to achieve conventional functionality and robustness while also supporting portability and mobility, bringing greater convenience and opportunity for its deployment in a wide range of operational environments from consumer applications to law enforcement. But achieving these aims brings new challenges such as issues with power consumption, algorithm complexity, device memory limitations, frequent changes in operational environment, security, durability, reliability, and connectivity. Mobile Biometrics provides a timely survey of the state of the art research and developments in this rapidly growing area.
Topics covered in Mobile Biometrics include mobile biometric sensor design, deep neural network for mobile person recognition with audio-visual signals, active authentication using facial attributes, fusion of shape and texture features for lip biometry in mobile devices, mobile device usage data as behavioral biometrics, continuous mobile authentication using user phone interaction, smartwatch-based gait biometrics, mobile four-fingers biometrics system, palm print recognition on mobile devices, periocular region for smartphone biometrics, and face anti-spoofing on mobile devices.
Topics covered in Mobile Biometrics include mobile biometric sensor design, deep neural network for mobile person recognition with audio-visual signals, active authentication using facial attributes, fusion of shape and texture features for lip biometry in mobile devices, mobile device usage data as behavioral biometrics, continuous mobile authentication using user phone interaction, smartwatch-based gait biometrics, mobile four-fingers biometrics system, palm print recognition on mobile devices, periocular region for smartphone biometrics, and face anti-spoofing on mobile devices.
More details
Series
Language
English
Place of publication
Stevenage
United Kingdom
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 236 mm
Width: 163 mm
Thickness: 30 mm
Weight
862 gr
ISBN-13
978-1-78561-095-0 (9781785610950)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Dr. Guodong Guo is Associate Professor in the Department of Computer Science and Electrical Engineering at West Virginia University, USA. He is also the Director and Founder of the Computer Vision Laboratory (CVL) at WVU, and affiliated with the Center for Identification Technology Research (CITeR), a unique national Biometric Research Center funded by the NSF.
Dr. Harry Wechsler is Professor of Computer Science at George Mason University (GMU) in Fairfax, VA, USA. He has been active in biometrics, face recognition, forensics and evidence analysis, smart identity and information management, contents-based image retrieval (CBIR), and cyber security, biomedical image processing, image analysis and understanding, data mining, machine learning and pattern recognition, with research funding from ARL, DARPA, DOD / TSWG, FBI, and NSF. He is an IEEE Fellow and an IAPR Fellow.
Dr. Harry Wechsler is Professor of Computer Science at George Mason University (GMU) in Fairfax, VA, USA. He has been active in biometrics, face recognition, forensics and evidence analysis, smart identity and information management, contents-based image retrieval (CBIR), and cyber security, biomedical image processing, image analysis and understanding, data mining, machine learning and pattern recognition, with research funding from ARL, DARPA, DOD / TSWG, FBI, and NSF. He is an IEEE Fellow and an IAPR Fellow.
Content
Chapter 1: Mobile biometrics
Chapter 2: Mobile biometric device design: history and challenges
Chapter 3: Challenges in developing mass-market mobile biometric sensors
Chapter 4: Deep neural networks for mobile person recognition with audio-visual signals
Chapter 5: Active authentication using facial attributes
Chapter 6: Fusion of shape and texture features for lip biometry in mobile devices
Chapter 7: Mobile device usage data as behavioral biometrics
Chapter 8: Continuous mobile authentication using user-phone interaction
Chapter 9: Smartwatch-based gait biometrics
Chapter 10: Toward practical mobile gait biometrics
Chapter 11: 4F (TM)-ID: mobile four-fingers biometrics system
Chapter 12: Palmprint recognition on mobile devices
Chapter 13: Addressing the presentation attacks using periocular region for smartphone biometrics
Chapter 14: Countermeasures to face photo spoofing attacks by exploiting structure and texture information from rotated face sequences
Chapter 15: Biometric antispoofing on mobile devices
Chapter 16: Biometric open protocol standard
Chapter 17: Big data and cloud identity service for mobile authentication
Chapter 18: Outlook for mobile biometrics
Chapter 2: Mobile biometric device design: history and challenges
Chapter 3: Challenges in developing mass-market mobile biometric sensors
Chapter 4: Deep neural networks for mobile person recognition with audio-visual signals
Chapter 5: Active authentication using facial attributes
Chapter 6: Fusion of shape and texture features for lip biometry in mobile devices
Chapter 7: Mobile device usage data as behavioral biometrics
Chapter 8: Continuous mobile authentication using user-phone interaction
Chapter 9: Smartwatch-based gait biometrics
Chapter 10: Toward practical mobile gait biometrics
Chapter 11: 4F (TM)-ID: mobile four-fingers biometrics system
Chapter 12: Palmprint recognition on mobile devices
Chapter 13: Addressing the presentation attacks using periocular region for smartphone biometrics
Chapter 14: Countermeasures to face photo spoofing attacks by exploiting structure and texture information from rotated face sequences
Chapter 15: Biometric antispoofing on mobile devices
Chapter 16: Biometric open protocol standard
Chapter 17: Big data and cloud identity service for mobile authentication
Chapter 18: Outlook for mobile biometrics