Toward an Asian-based bodily movement database for emotional communication.

Area of Science:

• Psychology
• Human-Computer Interaction
• Cultural Studies

Background:

• Existing bodily emotion expression databases are predominantly Western, leading to cultural bias.
• This bias risks skewing academic comprehension of human emotional expression.
• There is a need for culturally diverse datasets in emotion recognition research.

Purpose of the Study:

• To expand the repertoire of human bodily emotion expression databases.
• To address cultural biases in current emotion expression datasets.
• To develop a more culturally inclusive database for emotion recognition research.

Main Methods:

• Recruited Asian professional performers to wear motion-capture suits with 57 retroreflective markers.
• Actors expressed seven basic emotions through whole-body movements in a motion-capture lab.
• Participants judged perceived emotions from point-light displays derived from actor performances.

Main Results:

• Emotion discrimination accuracy from the new Asian dataset was comparable to Western databases.
• The novel approach using personalized, real-life scenarios effectively elicited emotions.
• The developed database demonstrates the viability of culturally diverse emotion expression data.

Conclusions:

• The study successfully created a culturally diverse database for bodily emotion expression.
• The novel emotional induction approach using personalized scenarios is effective.
• This database contributes to a more comprehensive, cross-cultural understanding of emotional expression.