Automated human emotion recognition from facial expressions is a well-studied problem
and still remains a very challenging task. Some efficient or accurate deep learning models …

This paper proposes an efficient approach for person-independent facial expression
recognition based on the fusion of Histogram of Oriented Gradients (HOG) descriptor and …

Facial expressions which contain rich behavioral information are the primary vehicle to
express emotions. It is important to analyze people's emotions with computer to achieve …

The ever-growing depth and width of Convolutional Neural Networks (CNNs) drastically
increases the number of their parameters and requires more powerful devices to train and …

Facial expressions are among the most powerful ways to reveal the emotional state.
Therefore, Facial Expression Recognition (FER) has been widely introduced to wide fields of …

A practical facial expression recognition system should be person-independent and robust
against factors such as noise and resolution. This paper handles these issues and offers a …

Abstract Automatic Facial Expression Recognition (FER) is an important research area in
computer vision because it has many real-time applications. However, the main issue lies in …

This paper proposes a novel descriptor for facial expression recognition called the Local
Directional Compact Pattern (LDCP), which encodes the prominent information of local …

The face expression recognition is used in countless application areas for example security,
computer vision and medical science etc. The facial expressions are used to communicate …

Facial expression recognition methods based on convolutional neural networks have greatly
improved the recognition accuracy. However, the feature information of face images has not …