利用相对视觉表现预测在适应亮度、观察者年龄、肤色、路面反射和人际距离变化下人际评价任务的表现

S. Fotios, Y. Mao, K. Hamoodh, C. Cheal
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引用次数: 0

摘要

本研究涉及行人道路照明。人们进行了许多实验,以确定光线的变化如何影响进行人际评价的能力,通常考虑到光线水平或光谱的变化。在这里,我们考虑另一种方法,使用现有的模型,相对视觉性能来预测性能。结果表明,人脸评价能力受适应亮度、路面反射率、观察者年龄和被观察者肤色的影响。以前的实验研究倾向于使用年轻的测试参与者来评估高加索人或亚洲人的脸:如果情况是让老年人来评估南非肤色的脸,那么目前的分析预测,为了达到最佳效果,光照水平需要增加一倍。
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Using relative visual performance to predict performance of an interpersonal evaluation task with variation in adaptation luminance, observer age, skin tone, pavement reflection and interpersonal distance
This study concerns road lighting for pedestrians. Many experiments have been conducted to determine how changes in lighting affect the ability to make interpersonal evaluations, usually considering variations in light level or light spectrum. Here, we consider an alternative approach, predicting performance using an existing model, Relative Visual Performance. The results show that face evaluation ability is affected by adaptation luminance, pavement surface reflectance, observer age, and skin tone of the observed person. Previous experimental studies have tended to use young test participants to evaluate Caucasian or Asian faces: if the situation instead involved an elderly person evaluating a face of South African skin tone, then the current analysis predicts that for optimal performance the light level would need to be doubled.
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