Face, Image, and Analysis

Abstract

Face image analysis, consisting of automatic investigation of images of (human) faces, is a hot research topic and a fruitful field. This introductory chapter discusses several aspects of the history and scope of face image analysis and provides an outline of research development publications of this domain. More prominently, different modules and some typical techniques for face image analysis are listed, explained, described, or summarized from a general technical point of view. One picture of the advancements and the front of this complex and prominent field is provided. Finally, several challenges and prominent development directions for the future are identified.

Age-invariant face recognition based on identity inference from appearance age

“…One of the earliest works on face recognition that describes a face with its within-individual and between-individual variations was introduced in [26] [27] [28]. Probabilistic Linear Discriminant Analysis (PLDA) [42] was employed to establish a generative linear model, and the optimal latent identity variable was iteratively derived by using the Expectation-Maximization (EM) [29] algorithm. This method was further applied to age-invariant face recognition in [21], where the within-individual variance was suitable for using the aging information, while the between-individual variation was suitable for using the identity information.…”