REVES/INRIA, Sophia Antipolis, France.
IEEE Trans Vis Comput Graph. 2011 Oct;17(10):1459-74. doi: 10.1109/TVCG.2010.236.
We present an image-based approach to relighting photographs of tree canopies. Our goal is to minimize capture overhead; thus the only input required is a set of photographs of the tree taken at a single time of day, while allowing relighting at any other time. We first analyze lighting in a tree canopy both theoretically and using simulations. From this analysis, we observe that tree canopy lighting is similar to volumetric illumination. We assume a single-scattering volumetric lighting model for tree canopies, and diffuse leaf reflectance; we validate our assumptions with synthetic renderings. We create a volumetric representation of the tree from 10-12 images taken at a single time of day and use a single-scattering participating media lighting model. An analytical sun and sky illumination model provides consistent representation of lighting for the captured input and unknown target times. We relight the input image by applying a ratio of the target and input time lighting representations. We compute this representation efficiently by simultaneously coding transmittance from the sky and to the eye in spherical harmonics. We validate our method by relighting images of synthetic trees and comparing to path-traced solutions. We also present results for photographs, validating with time-lapse ground truth sequences.
我们提出了一种基于图像的方法来重新照亮树冠的照片。我们的目标是最小化捕获开销;因此，唯一需要的输入是一组在一天中的单一时间拍摄的树木照片，同时允许在任何其他时间进行重新照明。我们首先从理论和模拟两方面分析树冠的照明。从这个分析中，我们观察到树冠的照明类似于体积照明。我们假设树冠的单一散射体积照明模型和漫反射叶反射率;我们用合成渲染来验证我们的假设。我们从一天中的单个时间拍摄的 10-12 张图像中创建树的体积表示，并使用单一散射参与介质照明模型。一个分析的太阳和天空照明模型为捕获的输入和未知目标时间提供一致的照明表示。我们通过应用目标和输入时间照明表示的比值来重新照亮输入图像。我们通过在球谐函数中同时对来自天空的和到眼睛的传输进行编码来有效地计算这个表示。我们通过重新照亮合成树木的图像并与路径追踪解决方案进行比较来验证我们的方法。我们还展示了照片的结果，并通过时移地面实况序列进行验证。
