A team led by Disney Research,
Zürich has developed a method to more efficiently render animated scenes that
involve fog, smoke or other substances that affect the travel of light,
significantly reducing the time necessary to produce high-quality images or
animations without grain or noise. The method, called joint importance
sampling, helps identify potential paths that light can take through a foggy or
underwater scene that are most likely to contribute to what the camera – and
the viewer – ultimately sees. In this way, less time is wasted computing paths
that aren't necessary to the final look of an animated sequence. Light rays are
deflected or scattered not only when they bounce off a solid object, but also
as they pass through aerosols and liquids. The effect of clear air is
negligible for rendering algorithms used to produce animated films, but
realistically producing scenes including fog, smoke, smog, rain, underwater
scenes, or even a glass of milk requires computational methods that account for
these participating media. So-called Monte Carlo algorithms are increasingly
being used to render such phenomena in animated films and special effects.
These methods operate by analyzing a random sampling of possible paths that
light might take through a scene and then averaging the results to create the
overall effect.
But researchers explained that
not all paths are created equal. Some paths end up being blocked by an object
or surface in the scene; in other cases, a light source may simply be too far
from the camera to have much chance of being seen. Calculating those paths can
be a waste of computing time or, worse, averaging them may introduce error, or
noise, that creates unwanted effects in the animation. Computer graphics researchers
have tried various ‘importance sampling’ techniques to increase the probability
that the random light paths calculated will ultimately contribute to the final
scene and keep noise to a minimum. Some techniques trace the light from its
source to the camera; others from the camera back to the source. Some are
bidirectional – tracing the light from both the camera and the source before
connecting them together. Unfortunately, even such sophisticated bidirectional
techniques compute the light and camera portions of the paths independently,
without knowledge of each other, before connecting them together, so they are
unlikely to construct full light paths that ultimately have a strong contribution
to the final image. By contrast, the joint importance sampling method developed
by the Disney Research team chooses the locations along the random paths with
mutual knowledge of the camera and light source locations.
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