A General Scattering Phase Function for Inverse Rendering

TL;DR

This paper introduces a new general scattering phase function for inverse rendering that overcomes limitations of empirical models, enabling more accurate modeling of diverse translucent materials through simulation and real-world tests.

Contribution

A novel positive-definite phase function is proposed, suitable for inverse rendering across various materials, addressing limitations of existing polynomial-based functions.

Findings

Successfully modeled a wide range of materials with Mie scattering theory

Accurately estimated scattering parameters in simulations and real-world experiments

Outperformed traditional empirical phase functions in versatility and accuracy

Abstract

We tackle the problem of modeling light scattering in homogeneous translucent material and estimating its scattering parameters. A scattering phase function is one of such parameters which affects the distribution of scattered radiation. It is the most complex and challenging parameter to be modeled in practice, and empirical phase functions are usually used. Empirical phase functions (such as Henyey-Greenstein (HG) phase function or its modified ones) are usually presented and limited to a specific range of scattering materials. This limitation raises concern for an inverse rendering problem where the target material is generally unknown. In such a situation, a more general phase function is preferred. Although there exists such a general phase function in the polynomial form using a basis such as Legendre polynomials \cite{Fowler1983}, inverse rendering with this phase function is not straightforward. This is because the base polynomials may be negative somewhere, while a phase function cannot. This research presents a novel general phase function that can avoid this issue and an inverse rendering application using this phase function. The proposed phase function was positively evaluated with a wide range of materials modeled with Mie scattering theory. The scattering parameters estimation with the proposed phase function was evaluated with simulation and real-world experiments.