A prerequisite for any function in social cognition is the perception and processing of social cues. Age estimation is a skill that is used in everyday life and is fundamental in social interactions. This study evaluated whether facial age estimation is impaired in patients with mild to moderate Alzheimer's disease (AD). The current age of faces is known to have an impact on age estimation, and...

Facial-image-based age estimation is being increasingly used in various fields. Examples include statistical marketing analysis based on age-specific product preferences, medical applications such as beauty products and telemedicine, age-based suspect tracking intelligent surveillance camera systems. Masks are worn for hygiene, personal privacy concerns, fashion. In particular, the acquisition ...

In this paper a new hierarchical age estimation method based on decision level fusion of global and local features is proposed. The shape and appearance information of human faces which are extracted with active appearance models (AAM) are used as global facial features. The local facial features are the wrinkle features extracted with Gabor filters and skin features extracted with local binary...

Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected...

Age estimation from facial images is typically cast as a nonlinear regression problem. The main challenge of this problem is the facial feature space w.r.t. ages is heterogeneous, due to the large variation in facial appearance across different persons of the same age and the nonstationary property of aging patterns. In this paper, we propose Deep Regression Forests (DRFs), an end-to-end model,...

Recently, the estimation of facial age has attracted much attention. This letter extends and improves a recently developed method (Guehairia et al., 2020) for fusing multiple deep features estimation. was based on random forests. We propose new pipeline that integrates tensor-based subspace learning before applying DRFs. Deep face training set are represented as 3D tensor. Multi-linear Whitened...