人工智能
皮肤颜色
面子(社会学概念)
计算机视觉
计算机科学
彩色视觉
原色
模式识别(心理学)
社会科学
社会学
作者
Boram Kim,Juhyun Lee,Sungmi Park,Hyeon-Jeong Suk
标识
DOI:10.1016/j.visres.2023.108247
摘要
This study investigated facial skin color differences before and after makeup. Toward this goal, a photo gauge, devised with a pair of color checkers as a reference, collected face images. In addition, color calibration and a deep-learning method extracted the color values of representative areas of facial skin. The photo gauge photographed 516 Chinese females before and after applying makeup. Then, the collected images were calibrated by referencing skin color patches, and the lower cheek regions' pixel colors were extracted using open-source computer vision libraries. Following the visible color spectrum of humans, the color values were computed in L*, a*, and b* of CIE1976L*a*b*. The results showed that the facial colors of the Chinese females changed to become brighter, less reddish, and less yellowish after applying the makeup, resulting in a paler skin tone. During the experiment, subjects were given five varieties of liquid foundation to choose one sample that best fits their skin. However, we failed to find any noticeable relationship between the individual's facial skin color characteristics and the liquid foundation selected. In addition, 55 subjects were identified according to their makeup use frequency and skill, but their color changes did not differ from the other subjects. This study provided quantitative evidence of makeup trends in the Shanghai region in China, and the method proposes a novel approach toward remote skin color research.
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