Application of Gaussian Process Preference Learning for Visualizing Facial Features Related to Personality Traits
Application of Gaussian Process Preference Learning for Visualizing Facial Features Related to Personality Traits
复制标题
高斯过程偏好学习在可视化与人格特质相关的面部特征中的应用
DOI：
10.1109/csde53843.2021.9718431
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Watanabe Katsumi
中科院分区：
文献类型：
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作者：
Shiroshita Keito;Komori Masashi;Nakamura Koyo;Kobayashi Maiko;Watanabe Katsumi
人们会根据他人的面部特征自动推断出他们的性格特征。本研究旨在应用基于贝叶斯优化（BO）的序贯实验设计，以阐明人格印象与面孔和面部特征之间的关系。我们使用了一个结合高斯过程偏好学习（GPPL）的BO，它允许我们基于成对比较任务来估计效用函数。106名日本大学生提供了照片，每个男性和女性的面部图像都被嵌入到StyleGAN 2网络中的潜在表示（18 x 512维）中，使用Flickr-Faces-HQ（FFHQ）数据集。使用PCA，潜在表征的维度被降低到8维子空间，我们称之为日本人脸空间。参与者被要求从第一次会议的图像中选择哪些面孔更值得信赖，并在第二次会议中选择更具优势的面孔。刺激图像是使用预先训练的StyleGAN 2模型在人脸空间内合成的。每届会议包括100项审判。前95次试验的每个会话的刺激是基于面部子空间中随机生成的参数创建的，而其余5次试验的刺激是基于使用采集函数计算的参数创建的。基于平均效用函数估计了与可信度和优势度相关的面部特征。可信度的印象被发现与面部厌恶，而优势与性二态性。结果表明，GPPL是一种有效的方法来阐明复杂刺激的平均心理评价。
People automatically make inferences about other people’s personality traits based on their facial features. This study aims to apply a sequential experimental design based on Bayesian optimization (BO) in order to elucidate the relationship between impressions of personality and faces and facial features. We used a BO that incorporates Gaussian process preference learning (GPPL) which allows us to estimate a utility function based on a pairwise comparison task. One hundred and six Japanese university students provided photographs and each male and female facial image was embedded into a latent representation (18 x 512 dimensions) in the StyleGAN2 network using the Flickr-Faces-HQ (FFHQ) dataset. Using PCA, the dimensions of the latent representations were reduced to an 8-dimensional subspace, which we refer to as the Japanese face space. The participants were asked to select which faces were more trustworthy from among the images in the first session and the more dominant faces in the second session. The stimulus images were synthesized using the pre-trained StyleGAN2 model within the face space. Each session consisted of 100 trials. The stimuli for each session of the first 95 trials were created based on randomly generated parameters in the face subspace, while the stimuli for the remaining five trials were created based on the parameters calculated using the acquisition function. Facial traits related to trustworthiness and dominance were estimated based on the averaged utility functions. The impression of trustworthiness was found to be associated with facial aversion, while dominance was associated with sexual dimorphism. The results suggest that GPPL is an effective method for elucidating average psychological evaluations of complex stimuli.