Human face analysis is an important task in computer vision. According to cognitive-psychological studies, facial dynamics could provide crucial cues for face analysis. In particular, the motion of facial local regions in facial expression is related to the motion of other facial regions. In this paper, a novel deep learning approach which exploits the relations of facial local dynamics has bee...

We propose a relative estimation method for subjective age, imaged by ourselves, using peoples' facial images and their chronological (real) age. We experimented with a rating scale for facial images which stimulated subjects. The subject evaluated an image as looking older than themselves with uncertainties. Finding the average values of the rating, the zero crossing point in the approximate l...

Facial age estimation is one of the unsolved challenging issues in automatic face perception. Previous studies usually formulated it as a classification problem, where each age is regarded as a class, or a regression problem where the age is regarded as a variable spanning in a real-valued interval. In this paper, we propose to formulate this task as an ordinal regression problem. On one hand, ...

Lack of sufficient training data with exact ages is still a challenge for facial age estimation. To deal with such problem, a method called Label Distribution Learning (LDL) was proposed to utilize the neighboring ages while learning a particular age. Later, an adaptive version of LDL called ALDL was proposed to generate a proper label distribution for each age. However, the adaptation process ...

In this paper, we propose a group-aware deep feature learning (GA-DFL) approach for facial age estimation. Unlike most existing methods which utilize hand-crafted descriptors for face representation, our GA-DFL method learns a discriminative feature descriptor per image directly from raw pixels for face representation under the deep convolutional neural networks framework. Motivated by the fact...

In this paper, we investigate and exploit the influence of facial expressions on automatic age estimation. Different from existing approaches, our method jointly learns the age and the expression by introducing a new graphical model with a latent layer between the age/expression labels and the features. This layer aims to learn the relationship between the age and the expression and captures th...

Facial aging, a new dimension that has recently been added to the problem of face recognition, poses interesting theoretical and practical challenges to the research community. The problem which originally generated interest in the psychophysics and human perception community, has recently found enhanced interest in the computer vision community. How do humans perceive age ? What constitutes an...

The problem of automatic age estimation from facial images poses a great number of challenges: uncontrollable environment, insufficient and incomplete training data, strong person-specificity, and high within-range variance, among others. These difficulties have made researchers of the field propose complex and strongly hand-crafted descriptors, which make it difficult to replicate and compare ...