Automatic machine-based Facial Expression Analysis (FEA) has made substantial progress
in the past few decades driven by its importance for applications in psychology, security …

Emotion is expressed in multiple modalities, yet most research has considered at most one
or two. This stems in part from the lack of large, diverse, well-annotated, multimodal …

This study proposes a novel automatic method for facial landmark localization relying on
geometrical properties of 3D facial surface working both on complete faces displaying …

Abstract 3D face was recently investigated for various applications, including biometrics and
diagnosis. Describing facial surface, ie how it bends and which kinds of patches is …

We present an approach utilizing Topological Data Analysis to study the structure of face
poses used in affective computing, ie, the process of recognizing human emotion. The …

Facial expression is an essential part in communication. It is a challenging task in computer
vision as well as in pattern recognition. Facial expression recognition has applications in …

The face attractiveness from 3D representation is still in the infancy stage. In this paper, we
investigate the role of 3D face geometry in facial beauty perception. Driven by heuristic …

In this paper, we propose a deformable synthesis model that can be used to synthesize data
to train deep neural networks for the task of emotion recognition. This model is created …

Faces captured in a real-world scenario may suffer from large variations in shape and
occlusions due to difference in illumination, variation in pose and orientation of a facial …

In this paper, we propose a novel method for 3D facial expression recognition based on a
statistical shape model with global and local constraints. We show that the combination of …