The performance of face analysis and recognition systems depends on the quality of the
acquired face data, which is influenced by numerous factors. Automatically assessing the …

The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …

Systems incorporating biometric technologies have become ubiquitous in personal,
commercial, and governmental identity management applications. Both cooperative (eg …

The large pose discrepancy between two face images is one of the fundamental challenges
in automatic face recognition. Conventional approaches to pose-invariant face recognition …

Biometrics, an integral component of Identity Science, is widely used in several large-scale-
county-wide projects to provide a meaningful way of recognizing individuals. Among existing …

Face image quality can be defined as a measure of the utility of a face image to automatic
face recognition. In this paper, we propose (and compare) two methods for learning face …

Biometric deals with the verification and identification of a person based on behavioural and
physiological traits. This article presents recent advances in physiological-based biometric …

The need for reliably determining the identity of a person is critical in a number of different
domains ranging from personal smartphones to border security; from autonomous vehicles …

End-to-end face quality assessment based on deep learning can directly predict the overall
quantitative score of face quality, thus hel** to control the risk of face recognition system …

Unmanned Aerial Vehicles (UAVs) or drones are often used to reach remote areas or
regions which are inaccessible to humans. Equipped with a large field of view, compact size …