Discriminative Approaches for Age Invariant Face Recognition: A Review

Age-invariant face recognition is a challenging and crucial aspect of face recognition. Over the past decade, researchers have primarily focused on recognizing faces in unconstrained environments, accounting for variations in pose, illumination, and expression. However, there is now a growing demand for age-invariant face recognition systems to address the identification of individuals with a significant age gap, including missing children or criminals, based on their facial images. In this paper, we present the latest discriminative approaches that highlight the advancements made in age-invariant face recognition in recent decades. We cover discriminative approaches utilized in this domain, which provide better results than generative approaches. The main objective of this paper is to offer researchers in this field a literature review of age-invariant face recognition, along with a general framework of discriminative methods.