ArticleScientific data2023
Multi-view emotional expressions dataset using 2D pose estimation.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Emotion recognition from body movement through interpretable motion-aware sequential modeling.Frontiers in artificial intelligence · 2026Article
- Emotion recognition in dance therapy driven by DanceEmoNet: a deep learning model based on facial expression and pose estimation.Frontiers in psychology · 2026Article
- Human Perception of the Emotional Expressions of Humanoid Robot Body Movements: Evidence from Survey and Eye-Tracking Measurements.Biomimetics (Basel, Switzerland) · 2024Article
- Emotional concepts shape the perceptual representation of body expressions.Human brain mapping · 2024Article
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7 authors.
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Abstract
Human body expressions convey emotional shifts and intentions of action and, in some cases, are even more effective than other emotion models. Despite many datasets of body expressions incorporating motion capture available, there is a lack of more widely distributed datasets regarding naturalized body expressions based on the 2D video. In this paper, therefore, we report the multi-view emotional expressions dataset (MEED) using 2D pose estimation. Twenty-two actors presented six emotional (anger, disgust, fear, happiness, sadness, surprise) and neutral body movements from three viewpoints (left, front, right). A total of 4102 videos were captured. The MEED consists of the corresponding pose estimation results (i.e., 397,809 PNG files and 397,809 JSON files). The size of MEED exceeds 150 GB. We believe this dataset will benefit the research in various fields, including affective computing, human-computer interaction, social neuroscience, and psychiatry.
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