Rendering

This talk complements a technical paper and focuses on implementation issues, including how our run time is designed to scale across many different platforms, from iPhones to modern GPUs.

In this paper, we derive a physically based model for simulating rainbows. Previous techniques for simulating rainbows have used either geometric optics (ray tracing) or Lorenz-Mie theory.

We present Virtual Beam Lights (VBLs), a progressive many-lights algorithm for rendering complex indirect transport paths in, from, and to media.

In this paper, we propose a parametric density estimation technique that represents radiance using a hierarchical Gaussian mixture.

We propose a novel density estimation technique that allows reusing sampled paths to reconstruct time-resolved radiance, and devise new sampling strategies that take into account the distribution of radiance along time in participating media.

Recent advances in rendering and data-driven animation have enabled the creation of compelling characters with impressive levels of realism. While data-driven techniques can produce animations that are extremely faithful to the original motion, many challenging problems remain because of the high complexity of human motion.

We propose a novel density estimation technique that allows reusing sampled paths to reconstruct time-resolved radiance, and devise new sampling strategies that take into account the distribution of radiance along time in participating media.

We present ratio tracking and residual tracking, two complementary techniques that can be combined into an efficient, unbiased estimator for evaluating transmittance in complex heterogeneous media.

We present a theoretical analysis of error of many combinations of Monte Carlo estimators used in image synthesis.

We organize this complex and active research area in a structure tailored to academic researchers, graduate students, and industry professionals alike.