Exploring facial traits associated with beauty and cuteness based on an alternative forced-choice task

Exploring facial traits associated with beauty and cuteness based on an alternative forced-choice task
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基于替代强制选择任务探索与美丽和可爱相关的面部特征

DOI:
10.1109/aciiw57231.2022.10086007
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发表时间:
2022
期刊:
2022 10th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
影响因子:
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通讯作者:
Watanabe Katsumi
Watanabe Katsumi
中科院分区:
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文献类型:
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作者:
Teraji Teppei;Shiroshita Keito;Komori Masashi;Nakamura Koyo;Kobayashi Maiko;Watanabe Katsumi

文献摘要

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有人强调,女性的面部吸引力可分为美丽和可爱等组成部分。与此同时,在日本文化中,也有人认为美丽和可爱之间的区别是模糊的。本研究通过高斯过程偏好学习(GPPL)估计多维面部特征的效用函数,阐明了美丽和可爱评价之间的异同。共有53名日本女大学生提供了面部照片。我们将每个女性面部图像嵌入到在Flickr-Faces-HQ数据集上训练的StyleGAN 2网络中的潜在表示中。使用主成分分析,维度的潜在表示减少到一个8维的子空间,我们称之为日本女性的脸空间。参与者被要求从面部空间中使用预先训练的StyleGAN 2模型合成的九张图像中选择最美丽/可爱的面孔。基于所有的偏好,参与者的心理效用函数估计使用GPPL。基于平均效用函数检验了与美丽和可爱相关的面部特征。结果显示,一些面部特征同时影响美丽和可爱。相比之下,一些与婴儿图式相关的面部特征与可爱有关,而一些面部特征只影响美丽。
It has been highlighted that female facial attractiveness is divisible into components such as beauty and cuteness. At the same time, in Japanese culture, it has also been suggested that the distinction between beauty and cuteness is ambiguous. This study clarified the similarities and differences between beauty and cuteness evaluations by estimating the utility functions of these for multi-dimensional facial traits using Gaussian process preference learning (GPPL). A total of 53 Japanese female university students provided facial photographs. We embedded each female facial image into the latent representation in the StyleGAN2 network trained on the Flickr-Faces-HQ dataset. Using principal component analysis, the dimension of the latent representations is reduced to an 8-dimensional subspace, which we refer to as the Japanese female face space. The participants were asked to select the most beautiful/cute faces from among the nine images that were synthesized using the pre-trained StyleGAN2 model from within the face space. Based on all preferences, participants' psychological utility functions were estimated using GPPL. Facial traits related to beauty and cuteness were examined based on the averaged utility functions. The results revealed that some facial traits affect both beauty and cuteness. In contrast, some baby schema-related facial traits were associated with cuteness, and some facial features affected only beauty.