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中国面部和身体数据集 (CFBD):同一个人的实验室和个人照片
Ying Hu1,2, Ruyu Pan3,4, Yaqi Xiao3,4
1State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China. huy@psych.ac.cn.
Behavior research methods
|September 20, 2025
概括
中国面部和身体数据集 (CFBD) 捕捉了模型内的关键面部变异性,增强了面部感知研究. 这一数据集显示,个人照片在吸引力和可信度方面比实验室照片的评分更高.
科学领域:
- 心理学 心理学 心理学
- 计算机视觉 计算机视觉
- 人与计算机的交互
背景情况:
- 面部感知研究往往忽视模型内部的变化,这对于稳定的面部表现至关重要.
- 现有的数据集主要集中在模型之间的差异上,限制了生态有效性.
研究的目的:
- 介绍中国面部和身体数据集 (CFBD),以捕捉广泛的模型内部面部变化.
- 提供一个研究面部感知在各种外观和图像条件的资源.
- 调查图像类型 (实验室与个人) 对特征感知的影响.
主要方法:
- 收集了来自117个人的2195张图像,包括实验室和个人照片.
- 对时间,表达,视角和上下文等属性进行编码的图像.
- 收集了参与者对吸引力,可信度和独特性的评级.
主要成果:
- CFBD在外观和图像属性上表现出广泛的变化.
- 在特征评分中的模型内部变异与模型之间的变异相似或大于模型之间的变异.
- 个人照片在吸引力,可信度和独特性方面比实验室照片获得更高的评分.
结论:
- CFBD为推进面部表达研究提供了宝贵的资源.
- 了解模型内部的变化对于开发强大的面部识别系统至关重要.
- 数据集突出了基于图像来源 (实验室与个人) 的感知差异.
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