Paper
10 October 2023 Joint prediction of discrete and continuous emotions from dance videos based on FFN
Jiang Huang, Xianglin Huang, Lifang Yang, Zhulin Tao
Author Affiliations +
Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127992J (2023) https://doi.org/10.1117/12.3005804
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
Dance performance provides an effective way to express human emotions. Compared with voice and facial expression, it is clear that the regularity of posture change is hard to capture. However, changes of posture can make emotional expressions more vivid in nature, which do well in the analysis of emotional states. In this paper, we propose a hybrid feature for emotion classification in dance performance by means of a well-designed feature fusion network. The novelty of this method is the joint prediction of discrete emotions and continuous emotions, which improves the accuracy and robustness of emotion recognition methods. Finally, we conduct experiments on the official dataset, and the effectiveness of our proposed method is clearly demonstrated through quantitative and qualitative experiments.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jiang Huang, Xianglin Huang, Lifang Yang, and Zhulin Tao "Joint prediction of discrete and continuous emotions from dance videos based on FFN", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127992J (10 October 2023); https://doi.org/10.1117/12.3005804
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KEYWORDS
Emotion

Video

3D modeling

Visualization

Education and training

Data modeling

Motion models

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