Bodily Expressed Emotion Understanding Through Integrating Laban Movement Analysis
Chenyan Wu (1), Dolzodmaa Davaasuren (1),
Tal Shafir (2), Rachelle Tsachor (3), James Z. Wang (1)
(1) The Pennsylvania State University, University Park, USA
(2) University of Haifa, Israel
(3) University of Illinois, Chicago, USA
Abstract:
Body movements carry important information about a person's emotions
or mental state and are essential in daily communication. Enhancing
the ability of machines to understand emotions expressed through body
language can improve the communication of assistive robots with
children and elderly users, provide psychiatric professionals with
quantitative diagnostic and prognostic assistance, and aid law
enforcement in identifying deception. This study develops a
high-quality human motor element dataset based on the Laban Movement
Analysis movement coding system and utilizes that to jointly learn
about motor elements and emotions. Our long-term ambition is to
integrate knowledge from computing, psychology, and performing arts to
enable automated understanding and analysis of emotion and mental
state through body language. This work serves as a launchpad for
further research into recognizing emotions through analysis of human
movement.
Full Paper
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Full Paper
(high-resolution PDF, arxiv.org, 4MB)
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Citation:
Chenyan Wu, Dolzodmaa Davaasuren, Tal Shafir, Rachelle Tsachor and
James Z. Wang, ``Bodily Expressed Emotion Understanding Through
Integrating Laban Movement Analysis,'' under major revision for
journal publication, 2023, arxiv.org/abs/2304.02187.
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Last Modified:
April 6, 2023
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