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Color correction of uncalibrated images for the classification of human skin color

机译:对人体肤色分类的unlalbriated图像的颜色校正

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Images of a scene captured with multiple cameras have different color values due to variations in capture and color rendering across devices. We present a method to accurately retrieve color information from uncalibrated images taken under uncontrolled lighting conditions with an unknown device and no access to raw data, but with a limited number of reference colors in the scene. The method is used to assess skin tones for cosmetics recommendations. A subject is imaged with a calibration target in the scene. This target is extracted and its color values are used to compute a color correction transform that is applied to the entire image. We establish that the best mapping is done using a target consisting of skin colored patches representing a range of human skin colors. We show that color information extracted from images is well correlated with color data derived from spectral measurements of skin. Skin color can be consistently assessed across cameras with different color rendering and resolutions ranging from 0.1 Mpixels to 4.0 Mpixels.
机译:由于设备捕获和颜色渲染的变化,具有多个摄像机捕获的场景的图像具有不同的颜色值。我们介绍了一种方法来精确地从不受控制的照明条件下拍摄的彩色信息,其中包括未知设备,并且无法访问原始数据,但是在场景中有有限数量的参考颜色。该方法用于评估化妆品建议的肤色。在场景中使用校准目标成像主题。提取该目标,其颜色值用于计算应用于整个图像的颜色校正变换。我们建立了使用由代表一系列人体肤色的皮肤色斑块组成的目标来完成最佳映射。我们表明,从图像中提取的颜色信息与来自皮肤光谱测量的颜色数据良好相关。在具有不同颜色渲染和0.1 mpixels至4.0 mpixels的不同颜色渲染和分辨率的情况下,可以始终如一地评估肤色。

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