Christoph Busch

TL;DR: The performance when the data is collected with a commercially available mobile device containing low-grade accelerometers, including the Google G1 phone containing the AK8976A embedded accelerometer sensor is reported.

TL;DR: This paper describes the various aspects of face presentation attacks, including different types of face artifacts, state-of-the-art PAD algorithms and an overview of the respective research labs working in this domain, vulnerability assessments and performance evaluation metrics, the outcomes of competitions, the availability of public databases for benchmarking new P AD algorithms in a reproducible manner, and a summary of the relevant international standardization in this field.

TL;DR: This survey categorise and summarise approaches to ear detection and recognition in 2D and 3D images, and provides an outlook over possible future research in the field of ear recognition, in the context of smart surveillance and forensic image analysis, which the authors consider to be the most important application ofEar recognition characteristic in the near future.

TL;DR: A conceptual categorization and metrics for an evaluation of such methods are presented, followed by a comprehensive survey of relevant publications, and technical considerations and tradeoffs of the surveyed methods are discussed.

TL;DR: This paper presents a novel approach that involves exploring the variation of the focus between multiple depth images rendered by the LFC that in turn can be used to reveal the presentation attacks.