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

机译:未校准图像的色彩校正,用于对人类肤色进行分类

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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:由于跨设备的捕获和颜色渲染有所不同,因此使用多台摄像机捕获的场景图像具有不同的颜色值。我们提出了一种方法,该方法可使用未知设备,无法访问原始数据,但场景中的参考色数量有限,从不受控制的照明条件下拍摄的未经校准的图像中准确检索颜色信息。该方法用于评估化妆品推荐的肤色。用场景中的校准目标对被摄对象成像。提取该目标并将其颜色值用于计算应用于整个图像的颜色校正变换。我们确定,最好的映射是使用由代表一系列人类皮肤颜色的皮肤色斑组成的目标完成的。我们表明,从图像中提取的颜色信息与从皮肤光谱测量得出的颜色数据具有很好的相关性。可以在具有0.1 Mpixels到4.0 Mpixels范围内的不同颜色渲染和分辨率的相机之间一致地评估肤色。

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