IEEE Trans Image Process. 2021;30:3610-3622. doi: 10.1109/TIP.2021.3061276. Epub 2021 Mar 17.
We propose objective, image-based techniques for quantitative evaluation of facial skin gloss that is consistent with human judgments. We use polarization photography to obtain separate images of surface and subsurface reflections, and rely on psychophysical studies to uncover and separate the influence of the two components on skin gloss perception. We capture images of facial skin at two levels, macro-scale (whole face) and meso-scale (skin patch), before and after cleansing. To generate a broad range of skin appearances for each subject, we apply photometric image transformations to the surface and subsurface reflection images. We then use linear regression to link statistics of the surface and subsurface reflections to the perceived gloss obtained in our empirical studies. The focus of this paper is on within-subject gloss perception, that is, on visual differences among images of the same subject. Our analysis shows that the contrast of the surface reflection has a strong positive influence on skin gloss perception, while the darkness of the subsurface reflection (skin tone) has a weaker positive effect on perceived gloss. We show that a regression model based on the concatenation of statistics from the two reflection images can successfully predict relative gloss differences.
我们提出了客观的、基于图像的方法来定量评估与人体判断一致的面部皮肤光泽度。我们使用偏光摄影术获取表面和次表面反射的单独图像，并依靠心理物理学研究来揭示和分离这两个组件对皮肤光泽度感知的影响。我们在清洁前后分别在宏观尺度（整个面部）和中观尺度（皮肤斑块）拍摄面部皮肤的图像。为了为每个受试者生成广泛的皮肤外观，我们对表面和次表面反射图像应用光度图像变换。然后，我们使用线性回归将表面和次表面反射的统计信息与我们的实证研究中获得的感知光泽度联系起来。本文的重点是受试者内光泽度感知，即同一受试者的图像之间的视觉差异。我们的分析表明，表面反射的对比度对皮肤光泽度感知有很强的正向影响，而次表面反射的暗度（肤色）对感知光泽度的影响较弱。我们表明，基于两个反射图像的统计信息串联的回归模型可以成功预测相对光泽度差异。
