ArticleScientific data2020
Kinematic dataset of actors expressing emotions.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- SIMBA: A robust and generalizable measure of data imbalance.Patterns (New York, N.Y.) · 2025Article
- An Emotion Recognition Method for Humanoid Robot Body Movements Based on a PSO-BP-RMSProp Neural Network.Sensors (Basel, Switzerland) · 2024Article
- 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
- Acting Emotions: a comprehensive dataset of elicited emotions.Scientific data · 2024Article
- A real-world dataset of group emotion experiences based on physiological data.Scientific data · 2024Article
- Multi-view emotional expressions dataset using 2D pose estimation.Scientific data · 2023Article
- A new kinematic dataset of lower limbs action for balance testing.Scientific data · 2023Article
- Kinematic dataset of actors expressing emotions.Scientific data · 2020Article
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Authors and funding
13 authors.
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Abstract
Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics.
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