Facial soft biometrics : Methods, applications, and solutions

This dissertation studies soft biometrics traits, their applicability in different security and commercial scenarios, as well as related usability aspects. We place the emphasis on human facial soft biometric traits which constitute the set of physical, adhered or behavioral human characteristics that can partially differentiate, classify and identify humans. Such traits, which include characteristics like age, gender, hair, skin and eye color, the presence of glasses, moustache or beard, inherit several advantages such as ease of acquisition, as well as a natural compatibility with how humans perceive their surroundings.
Specifically, soft biometric traits are compatible with the human process of classifying and recalling our environment, a process which involves constructions of hierarchical structures of different refined traits.
This thesis explores these traits, and their application in soft biometric systems (SBSs), and specifically focuses on how such systems can achieve different goals including database search pruning, human identification, human re-identification and, on a different note, prediction and quantification of facial aesthetics. Our motivation originates from the emerging importance of such applications in our evolving society, as well as from the practicality of such systems. SBSs generally benefit from the non-intrusive nature of acquiring soft biometric traits, and enjoy computational efficiency which in turn allows for fast, enrolment-free and pose-flexible biometric analysis, even in the absence consent and cooperation by the involved human subjects. These benefits render soft biometrics indispensable in applications that involve processing of real life images and videos.