论文标题
在RGB虚拟生产阶段共同优化颜色演绎和相机内背景
Jointly Optimizing Color Rendition and In-Camera Backgrounds in an RGB Virtual Production Stage
论文作者
论文摘要
虽然虚拟生产系统中使用的LED面板可以显示带有宽色域的鲜艳的图像，但由于其狭窄的红色，绿色和蓝色LED的峰值光谱输出，它们在用作照明时会产生有问题的色移。在这项工作中，我们为虚拟生产阶段提供了改进的颜色校准过程，可以改善此颜色演绎问题，同时还通过准确的相机内背景颜色。我们通过优化相机视野中可见的LED面板像素来优化线性色彩校正转换，2）相机视野外的像素照亮了受试者，以及作为后过程，3）相机记录的像素值。结果是，在RGB LED面板虚拟生产阶段拍摄的镜头可以表现出更准确的肤色和服装颜色，同时仍然重现相机内背景的所需颜色。
While the LED panels used in virtual production systems can display vibrant imagery with a wide color gamut, they produce problematic color shifts when used as lighting due to their peaky spectral output from narrow-band red, green, and blue LEDs. In this work, we present an improved color calibration process for virtual production stages which ameliorates this color rendition problem while also passing through accurate in-camera background colors. We do this by optimizing linear color correction transformations for 1) the LED panel pixels visible in the field of view of the camera, 2) the pixels outside the field of view of the camera illuminating the subjects, and, as a post-process, 3) the pixel values recorded by the camera. The result is that footage shot in an RGB LED panel virtual production stage can exhibit more accurate skin tones and costume colors while still reproducing the desired colors of the in-camera background.
