IEEE Transactions on Affective Computing

In The formative years of Affective Computing [1], from the late 1990s and into the early 2000s, a significant fraction of research attention was focused on the development of methods for <italic>unobtrusive physiological measurement</italic>. It quickly ...

Emotion plays a critical role in making the computer more human-like. As the first and most essential step, emotion recognition emerges recently as a hot but relatively nascent topic, i.e., current research mainly focuses on single modality (e.g., facial ...

Emotional arousal, an essential dimension of game users&#x2019; experience, plays a crucial role in determining whether a game is successful. Game users&#x2019; emotion arousal assessment (GUEA) is of great importance. However, GUEA often faces challenges,...

Depression is a critical problem in modern society that affects an estimated 350 million people worldwide, causing feelings of sadness and a lack of interest and pleasure. Emotional disorders are gaining interest and are closely entwined with depression, ...

During group interactions, we react and modulate our emotions and behaviour to the group through phenomena including emotion contagion and physiological synchrony. Previous work on emotion recognition through video/image has shown that group context ...

Emotions are multifaceted phenomena that affect our behaviour, perception, and cognition. Increasing evidence indicates that induction mechanisms play a crucial role in triggering emotions by simulating the sensations required for an experimental design. ...

The long-lasting global pandemic of Coronavirus disease 2019 (COVID-19) has changed our daily life in many ways and put heavy burden on our mental health. Having a predictive model of negative emotions during COVID-19 is of great importance for ...

As one of the most important affective signals, facial affect analysis (FAA) is essential for developing human-computer interaction systems. Early methods focus on extracting appearance and geometry features associated with human affects while ignoring ...

The rapid development and ubiquity of mobile and wearable devices promises to enable researchers to monitor users&#x2019; granular emotional data in a less intrusive manner. Researchers have used a wide variety of mobile and wearable devices for this ...

Many areas in computer science are facing the need to analyze, quantify and reproduce movements expressing emotions. This paper presents a systematic review of the intelligible factors involved in the expression of emotions in human movement and posture. ...

Empathy is a vital factor that contributes to mutual understanding, and joint problem-solving. In recent years, a growing number of studies have recognized the benefits of empathy and started to incorporate empathy in conversational systems. We refer to ...

Automatic emotion recognition based on electroencephalogram (EEG) has attracted rapidly increasing interests. Due to large inter-subject variabilities, subject-independent emotion recognition faces great challenges. Recently, domain adaptation methods ...

Facial expression recognition (FER) is of great interest to the current studies of human-computer interaction. In this paper, we propose a novel geometry-guided facial expression recognition framework, based on graph convolutional networks and ...

Spatial navigation is an important aspect of everyday life but may be negatively impacted by both cognitive and affective load. Cognitive and affective load may be measured via autonomic arousal and increased load may lead to reduced navigational ...

Sentiment analysis is an important research field aiming to extract and fuse sentimental information from human utterances. Due to the diversity of human sentiment, analyzing from multiple modalities is usually more accurate than from a single modality. ...

With the increasing use of social media with its ability for users to share comments immediately, the extent of a system to identify offensive content has become a necessity in all languages. Due to the lack of publicly available resources on offensive ...

When a multi-modal affective analysis model generalizes from a bimodal task to a trimodal or multi-modal task, it is usually transformed into a hierarchical fusion model based on every two pairwise modalities, similar to a binary tree structure. This ...

Emotion recognition is a key attribute for artificial intelligence systems that need to naturally interact with humans. However, the task definition is still an open problem due to the inherent ambiguity of emotions. In this paper, a novel Bayesian ...

Depression is a common psychiatric disorder worldwide. However, in China, a considerable number of patients with depression are not diagnosed, and most of them are not aware of their depression. Despite increasing efforts, the goal of automatic depression ...

Aspect category level sentiment analysis aims to identify the sentiment polarities towards the aspect categories discussed in a sentence. It usually suffers from a lack of labeled data. A popular solution is to transfer knowledge from a labeled source ...

Affective computing strives to recognize a person&#x0027;s affective state (e.g., emotion, mood) based on what can be observed. However, electroencephalogram (EEG) and video technologies have not been widely adopted for daily life affect monitoring due to ...

Frustration is an unpleasant emotion prevalent in several target applications of affective computing, such as human-machine interaction, learning, (online) customer interaction, and gaming. One idea to redeem this issue is to recognize frustration to ...

Action Units (AU) are muscular activations used to describe facial expressions. Therefore accurate AU recognition unlocks unbiaised face representation which can improve face-based affective computing applications. From a learning standpoint AU detection ...

Text, visual, and acoustic are usually complementary in the Multimodal Sentiment Analysis (MSA) task. However, current methods primarily concern shared representations while neglecting the critical private aspects of data within individual modalities. In ...

The quality of daily spontaneous conversations is of importance towards both our well-being as well as the development of interactive social agents. Prior research directly studying the quality of social conversations has operationalized it in narrow ...

We consider the problem of inferring what happened to a person in a social task from momentary facial reactions. To approach this, we introduce several innovations. First, rather than predicting what (observers think) someone feels, we predict objective ...

Emotional information plays an important role in various multimedia applications. Movies, as a widely available form of multimedia content, can induce multiple positive emotions and stimulate people&#x0027;s pursuit of a better life. Different from ...

The antagonistic behavior in the crowd usually exacerbates the seriousness of the situation in sudden riots, where the antagonistic emotional contagion and behavioral decision making play very important roles. However, the complex mechanism of ...

This article introduces a novel preference learning framework that simultaneously considers both the intended and the perceived labels while addressing the mismatches between them. Based on analyzing the discrepancies and agreements between the intended ...

Negative emotions may induce dangerous driving behaviors leading to extremely serious traffic accidents. Therefore, it is necessary to establish a system that can automatically recognize driver emotions so that some actions can be taken to avoid traffic ...