相关论文: Discovering Gender Differences in Facial Emotion R…

We present a Fourier-based machine learning technique that characterizes and detects facial emotions. The main challenging task in the development of machine learning (ML) models for classifying facial emotions is the detection of accurate…

In this paper we address the problem of multi-cue affect recognition in challenging scenarios such as child-robot interaction. Towards this goal we propose a method for automatic recognition of affect that leverages body expressions…

Emotion recognition based on physiological signals is a hot topic and has a wide range of applications, like safe driving, health care and creating a secure society. This paper introduces a physiological dataset PAFEW, which is obtained…

Depression is a common mental health disorder that can cause consequential symptoms with continuously depressed mood that leads to emotional distress. One category of depression is Concealed Depression, where patients intentionally or…

Studies in the area of neuroscience have revealed the relationship between emotional patterns and brain functional regions, demonstrating that dynamic relationships between different brain regions are an essential factor affecting emotion…

Emotion recognition is essential for applications in affective computing and behavioral prediction, but conventional systems relying on single-modality data often fail to capture the complexity of affective states. To address this…

In this paper, we present an approach based on convolutional neural networks (CNNs) for facial expression recognition in a difficult setting with severe occlusions. More specifically, our task is to recognize the facial expression of a…

Throughout the past decade, many studies have classified human emotions using only a single sensing modality such as face video, electroencephalogram (EEG), electrocardiogram (ECG), galvanic skin response (GSR), etc. The results of these…

Automatic recognition of emotion from facial expressions is an intense area of research, with a potentially long list of important application. Yet, the study of emotion requires knowing which facial expressions are used within and across…

In human interactions, emotion recognition is crucial. For this reason, the topic of computer-vision approaches for automatic emotion recognition is currently being extensively researched. Processing multi-channel electroencephalogram (EEG)…

Applications of an efficient emotion recognition system can be found in several domains such as medicine, driver fatigue surveillance, social robotics, and human-computer interaction. Appraising human emotional states, behaviors, and…

Existing facial expression recognition (FER) methods typically fine-tune a pre-trained visual encoder using discrete labels. However, this form of supervision limits to specify the emotional concept of different facial expressions. In this…

Emotions play an essential role in human communication. Developing computer vision models for automatic recognition of emotion expression can aid in a variety of domains, including robotics, digital behavioral healthcare, and media…

In our multicultural world, affect-aware AI systems that support humans need the ability to perceive affect across variations in emotion expression patterns across cultures. These systems must perform well in cultural contexts without…

Facial expressions are one of the most powerful, natural and immediate means for human being to communicate their emotions and intensions. Recognition of facial expression has many applications including human-computer interaction,…

Facial emotion recognition is the task to classify human emotions in face images. It is a difficult task due to high aleatoric uncertainty and visual ambiguity. A large part of the literature aims to show progress by increasing accuracy on…

Current expressive avatar systems rely heavily on visual cues, failing when faces are occluded or when emotions remain internal. We present Mind-to-Face, the first framework that decodes non-invasive electroencephalogram (EEG) signals…

Introduction: Music provides an incredible avenue for individuals to express their thoughts and emotions, while also serving as a delightful mode of entertainment for enthusiasts and music lovers. Objectives: This paper presents a…

Emotion recognition using EEG signals is an emerging area of research due to its broad applicability in BCI. Emotional feelings are hard to stimulate in the lab. Emotions do not last long, yet they need enough context to be perceived and…

An advanced emotion classification model was developed using a CNN-Transformer architecture for emotion recognition from EEG brain wave signals, effectively distinguishing among three emotional states, positive, neutral and negative. The…