基于真实皮肤模型的面部红肿感知

Yan Lu, Kaida Xiao, Cheng Li
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引用次数: 0

摘要

面部发红是一种重要的感知属性,受到皮肤病学和化妆品等应用领域的广泛关注。现有研究通常使用面部皮肤面积的平均CIELAB a*值来表示面部的整体发红程度。然而,对面部发红的感知从未被精确地研究过。本研究旨在量化对面部发红的感知,同时探讨面部与均匀斑块之间的感知差异。一组观察者根据他们感知到的红色程度对80张真实人脸和均匀肤色斑块的图像进行了缩放。结果表明,CIELAB a*并不能很好地预测面部发红,因为感知到的发红也受到L*和b*值的影响。研究人员开发了一个新的指标RIS来准确量化面部皮肤发红的感觉,其准确度(R2 = 0.874)远高于A *值(R2 = 0.461)。讨论了面部发红和斑块发红的感知差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Facial Redness Perception based on Realistic Skin Models
Facial redness is an important perceptual attribute that receives many concerns from application fields such as dermatology and cosmetics. Existing studies have commonly used the average CIELAB a* value of the facial skin area to represent the overall facial redness. Yet, the perception of facial redness has never been precisely examined. This research was designed to quantify the perception of facial redness and meanwhile investigate the perceptual difference between the faces and the uniform patches. Eighty images of real human faces and uniform skin colour patches were scaled in terms of their perceived redness by a panel of observers. The results showed that the CIELAB a* was not a good predictor of facial redness since the perceived redness was also affected by the L* and b* values. A new index, RIS was developed to accurately quantify the perception of facial skin redness, which promised a much higher accuracy (R2 = 0.874) than the a* value (R2 = 0.461). The perceptual differenc between facial redness and patch redness was also discussed.
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