通过自动化面部动作单元分析来感知情感价值和兴奋动态
Junyao Zhang1, Wataru Sato2, Naoya Kawamura1
1Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo, Kyoto, 606-8507, Japan.
Scientific reports
|August 22, 2024
概括
来自视频的自动化面部表情分析可以估计动态情绪状态. 这项研究表明,特定的面部动作单元与主观价值和兴奋相关,并提供了实际应用.
科学领域:
- 心理学 心理学 心理学
- 计算机科学 计算机科学
- 情感计算是一种情感计算.
背景情况:
- 使用客观信号来估计动态情绪体验是有价值的.
- 之前的研究使用了面部肌肉的电肌图 (EMG) 来追踪价值.
- 基于视频的非侵入性面部动作分析对情绪动态的实用性仍然未被探索.
研究的目的:
- 调查面部表情的自动视频分析是否可以捕捉动态情绪状态.
- 为了确定特定的面部动作单位 (AU) 和主观的价值/唤醒等级之间的相关性.
- 探索面部动作与情感动态之间的非线性关系.
主要方法:
- 参与者在观看情感电影时录制了面部视频.
- 动态价值和兴奋评级同时收集.
- 使用SHapley添加剂扩展的自动面部动作单元检测和随机森林回归.
主要成果:
- 行动单元04 (下降眉毛) 与价值负相关;行动单元12 (拉唇角) 与价值正相关.
- 其他AU显示与动态价值或兴奋的相关性.
- 通过建模,确定了AU和情绪动态之间的非线性关联.
结论:
- 从视频数据中对面部表情的自动分析可以有效地估计动态情绪状态.
- 这种方法在心理健康,安全和教育领域都有潜在的应用.
- 面部动作单元动态提供了主观情绪体验的客观相关性.
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