Dance Emotion Recognition Based on Laban Motion Analysis Using Convolutional Neural Network and Long Short-Term Memory Article Swipe
Simin Wang
,
Junhuai Li
,
Ting Cao
,
Huaijun Wang
,
Pengjia Tu
,
Yue Li
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/access.2020.3007956
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/access.2020.3007956
Dance emotion recognition technology is of great significance for the digitalization, virtual performance, inheritance and protection of folk dance. Based on the mechanism that emotion expression in dance performance can be fully expressed through the strength and rhythm of dance movements, a novel dance emotion expression method is proposed to train hybrid deep learning neural network, to effectively identify the seven basic dance emotions of fear, anger, boredom, excitement, joy, relaxation and sadness. First, in order to fully express the emotions contained in the dance movements, this paper defines a dance emotion expression method through Laban Movement Analysis (LMA) method, which includes the characteristic parameters of the three aspects of body structure, spatial orientation and force effect, and converts the original dance movement data into three characteristic expression parameters to obtain dance emotion data. Then, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) hybrid neural network models are used to test and train dance emotion data. Finally, in order to verify the applicability of the CNN-LSTM model, decision tree, random forest, CNN and LSTM are established and compared for accuracy. The results show that it is feasible to identify dance emotion from the perspective of dance movement, and the CNN-LSTM model is of high accuracy.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2020.3007956
- https://ieeexplore.ieee.org/ielx7/6287639/8948470/09136698.pdf
- OA Status
- gold
- Cited By
- 48
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3041751009
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- OpenAlex ID
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https://openalex.org/W3041751009Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2020.3007956Digital Object Identifier
- Title
-
Dance Emotion Recognition Based on Laban Motion Analysis Using Convolutional Neural Network and Long Short-Term MemoryWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Simin Wang, Junhuai Li, Ting Cao, Huaijun Wang, Pengjia Tu, Yue LiList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2020.3007956Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/8948470/09136698.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/8948470/09136698.pdfDirect OA link when available
- Concepts
-
Dance, Artificial intelligence, Computer science, Convolutional neural network, Sadness, Artificial neural network, Deep learning, Speech recognition, Computer vision, Anger, Psychology, Visual arts, Art, PsychiatryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
48Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 11, 2023: 14, 2022: 9, 2021: 5Per-year citation counts (last 5 years)
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35Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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