Photo-consistent reconstruction of semitransparent scenes by density-sheet decomposition

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.