自动面部表情识别中的跨种族效应违反了测量不变性
Yen-Ting Li1, Su-Ling Yeh1,2,3,4, Tsung-Ren Huang1,2,3,4
1Department of Psychology, National Taiwan University, Taipei City, Taiwan.
Frontiers in psychology
|December 22, 2023
概括
自动面部情绪识别系统显示对东方面部的偏见,影响跨文化研究. 然而,幸福的认知仍然准确跨种族,适合积极心理学研究.
科学领域:
- 心理学 心理学 心理学
- 认知神经科学 认知神经科学
- 计算机视觉 计算机视觉
背景情况:
- 面部情绪识别 (FER) 研究越来越多地使用自动化方法.
- 自动FER提供对大型数据集的客观,快速分析.
- 有关在西方人脸上训练的模型对其他人口的普遍性存在担忧.
研究的目的:
- 执行流行面部情绪识别系统 (FaceReader,DeepFace) 的跨种族验证.
- 评估这些系统在西方和东方面部数据集上的性能.
- 调查跨文化的自动情绪识别中的潜在偏见.
主要方法:
- 使用了两个流行的自动面部情绪识别系统:FaceReader和DeepFace.
- 使用两个西方和两个东方面部数据集进行跨种族验证.
- 评估了系统在识别情绪类别中的准确性.
主要成果:
- 这两种系统在西方数据集上都取得了高精度,但在东方数据集上表现不佳.
- 对负面情绪的识别精度在东方人脸上特别降低.
- 测量幸福感的结果在不同种族群体中都准确且不变.
结论:
- 自动FER系统可能会表现出种族偏见,警告在涉及非西方面孔的跨文化研究中使用它们.
- 尽管有局限性,但这些系统的幸福度测量对于跨文化积极心理学研究是可靠的.
- 未来的研究应该专注于开发更多文化不变的FER模型.
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