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Photo-Consistent Reconstruction of Semitransparent Scenes by Density-Sheet Decomposition

机译:光密度分解法半透明场景的光一致性重构

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This paper considers the problem of reconstructing visually realistic 3D models of dynamic semitransparent scenes, such as fire, from a very small set of simultaneous views (even two). We show that this problem is equivalent to a severely underconstrained computerized tomography problem, for which traditional methods break down. Our approach is based on the observation that every pair of photographs of a semitransparent scene defines a unique density field, called a Density Sheet, that 1) concentrates all its density on one connected, semitransparent surface, 2) reproduces the two photos exactly, and 3) is the most spatially compact density field that does so. From this observation, we reduce reconstruction to the convex combination of sheet-like density fields, each of which is derived from the Density Sheet of two input views. We have applied this method specifically to the problem of reconstructing 3D models of fire. Experimental results suggest that this method enables high-quality view synthesis without overfitting artifacts.
机译:本文考虑了从很小的一组同时视图(甚至两个)重建动态半透明场景(例如火)的视觉逼真的3D模型的问题。我们表明,这个问题等同于严重受限的计算机断层摄影问题,传统方法无法解决该问题。我们的方法基于以下观察结果:半透明场景的每对照片都定义了一个唯一的密度场,称为密度表,该密度场是:1)将所有密度集中在一个连接的半透明表面上; 2)精确地复制了两张照片,并且3)是在空间上最紧凑的密度场。从该观察结果中,我们将重建简化为片状密度场的凸组合,每个密度场均源自两个输入视图的“密度表”。我们将这种方法专门应用于重建3D火模型的问题。实验结果表明,该方法可以实现高质量的视图合成,而不会过度拟合伪影。

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