Mobile Biometrics

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Editors: Guodong Guo 1 ; Harry Wechsler 2
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Publication Year: 2017

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.

Inspec keywords: biometrics (access control); cloud computing; security of data; mobile computing

Other keywords: biometric antispoofing; audio-visual signals; cloud identity service; active authentication; mobile four-finger biometrics system; face photo spoofing attacks; mobile person recognition; behavioral biometrics; facial attributes; smart phone biometrics; lip biometry; smart watch-based gait biometrics; periocular region; user-phone interaction; biometric open protocol standard; texture feature fusion; palmprint recognition; mobile authentication; shape feature fusion; rotated face sequences; deep neural networks; presentation attacks; Big Data

Subjects: Cryptography; General electrical engineering topics; Internet software; General and management topics; Image recognition; Computer vision and image processing techniques; Ubiquitous and pervasive computing; Data security

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