With the use of primaries which have increasingly narrow bandwidths in modern displays, observer metameric breakdown is becoming a significant factor. This can lead to discrepancies in the perceived color between different observers. If the spectral sensitivity of a user's eyes could be easily measured, next generation displays would be able to adjust the display content to ensure that the colors are perceived as intended by a given observer. We present a mathematical framework for calculating spectral sensitivities of a given human observer using a color matching experiment that could be done on a mobile phone display. This forgoes the need for expensive in-person experiments and allows system designers to easily calibrate displays to match the user's vision, in-the-wild. We show how to use sRGB pixel values along with a simple display model to calculate plausible color matching functions (CMFs) for the users of a given display device (e.g., a mobile phone). We evaluate the effect of different regularization functions on the shape of the calculated CMFs and the results show that a sum of squares regularizer is able to predict smooth and qualitatively realistic CMFs.

中文翻译：

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从视频游戏数据推断人类观察者的光谱敏感性

随着在现代显示器中使用带宽越来越窄的原色，观察者同色异谱分解正成为一个重要因素。这可能导致不同观察者之间感知颜色的差异。如果可以轻松测量用户眼睛的光谱灵敏度，下一代显示器将能够调整显示内容以确保给定观察者所感知的颜色。我们提出了一个数学框架，用于使用可以在手机显示屏上进行的颜色匹配实验来计算给定人类观察者的光谱灵敏度。这无需进行昂贵的现场实验，并允许系统设计人员轻松校准显示器以匹配用户的视觉，在野外。我们展示了如何使用 sRGB 像素值和一个简单的显示模型来计算给定显示设备（例如，移动电话）的用户的合理颜色匹配函数 (CMF)。我们评估了不同正则化函数对计算出的 CMF 形状的影响，结果表明平方和正则化器能够预测平滑且定性逼真的 CMF。