László Szirmay-Kalos, Iliyan Georgiev, Milán Magdics, Balázs Molnár, and Dávid Légrády
Department of Control Engineering and Information Technology, Technical
University of Budapest,
Budapest, Magyar tudósok krt.
2, H-1117, HUNGARY;
szirmay@iit.bme.hu
Solid Angle, email: iliyan@solidangle.com
Abstract:
This paper presents a new
stochastic particle model for efficient and unbiased Monte Carlo rendering of
heterogeneous participating media.We randomly add and
remove material particles to obtain a density with which free flight sampling
and transmittance estimation are simple, while material particle properties are
simultaneously modified to maintain the true expectation of the radiance. We show
that meeting this requirement may need the introduction of light particles with
negative energy and materials with negative extinction, and provide an
intuitive interpretation for such phenomena. Unlike previous unbiased methods,
the proposed approach does not require a-priori knowledge of the maximum medium
density that is typically difficult to obtain for procedural models. However,
the method can benefit from an approximate knowledge of the density, which can
usually be acquired on-the-fly at little extra cost and can greatly reduce the
variance of the proposed estimators. The introduced mechanism can be integrated
in participating media renderers where transmittance estimation and free flight
sampling are building blocks. We demonstrate its application in a multiple
scattering particle tracer, in transmittance computation, and in the estimation
of the inhomogeneous air-light integral.
Keywords:
Participating media, transmittance,
free path sampling, Woodcock tracking, Monte Carlo method, Volumetric
global illumination, procedural models, Perlin noise.