Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Affective computing, as its name implies, focuses on the recognition of human emotions,
sentiments, and feelings. This interdisciplinary field encompasses diverse areas such as …

With the development of intelligent automotive human-machine systems, driver emotion
detection and recognition has become an emerging research topic. Facial expression-based …

Recent research has shown that facial expressions and body gestures are two significant
implications in identifying human emotions. However, these studies mainly focus on …

Emotions can be perceived from a person's gait, ie, their walking style. Existing methods on
gait emotion recognition mainly leverage the posture information as input, but ignore the …

Understanding emotions from diverse contexts has received widespread attention in
computer vision communities. The core philosophy of Context-Aware Emotion Recognition …

The existence of emotion-irrelevant representations and individual variability impedes the
extraction of robust emotional representations, limiting the adaptability of EEG emotion …

Emotion recognition from physiological signals is a topic of widespread interest, and
researchers continue to develop novel techniques for perceiving emotions. However, the …

Recognizing activities from egocentric multimodal data collected by wearable cameras and
sensors, is gaining interest, as multimodal methods always benefit from the complementarity …

In recent years, emotion recognition has received significant attention, presenting a plethora
of opportunities for application in diverse fields such as human–computer interaction …