In this paper, a novel deep neural network (DNN)-driven feature learning method is
proposed and applied to multi-view facial expression recognition (FER). In this method …

Images of facial expressions are often captured from various views as a result of either head
movements or variable camera position. Existing methods for multiview and/or view …

Recognition of natural emotions from human faces is an interesting topic with a wide range
of potential applications, such as human-computer interaction, automated tutoring systems …

Covariance matrices have found success in several computer vision applications, including
activity recognition, visual surveillance, and diffusion tensor imaging. This is because they …

In the past few years, facial features detection and landmarks analysis plays a vital role in
several practical application such as surveillance system, crime detector and age estimation …

We propose a method for head-pose invariant facial expression recognition that is based on
a set of characteristic facial points. To achieve head-pose invariance, we propose the …

In this paper, a novel multi-view facial expression recognition method is presented. Different
from most of the facial expression methods that use one view of facial feature vectors in the …

Abstract Art is imaginative human creation meant to be appreciated, make people think, and
evoke an emotional response. Here for the first time, we create a dataset of more than 4,000 …

Multiview Facial Expression Recognition (MFER) is a well-known interdisciplinary problem
among computer science and related disciplines with promising and valuable applications …

Local edge-based descriptors have gained much attention as feature extraction methods for
facial expression recognition. However, such descriptors are found to suffer from unstable …