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.
