View-Independent Adjoint Light Tracing for Lighting Design Optimization

Kavli Affiliate: Michael Wimmer

| First 5 Authors: Lukas Lipp, David Hahn, Pierre Ecormier-Nocca, Florian Rist, Michael Wimmer

| Summary:

Controlling light is a central element when composing a scene, enabling
artistic expression, as well as the design of comfortable living spaces. In
contrast to previous camera-based inverse rendering approaches, we introduce a
novel method for interactive, view-independent differentiable global
illumination. Our method first performs a forward light-tracing pass, starting
from the light sources and storing the resulting radiance field on the scene
geometry, representing specular highlights via hemi-spherical harmonics. We
then evaluate an objective function on the entire radiance data and propagate
derivatives back to the lighting parameters by formulating a novel, analytical
adjoint light-tracing step. Our method builds on GPU ray tracing, which allows
us to optimize all lighting parameters at interactive rates, even for complex
geometry. Instead of specifying optimization targets as view-specific images,
our method allows us to optimize the lighting of an entire scene to match
either baked illumination (e.g., lightmaps), regulatory lighting requirements
for work spaces, or artistic sketches drawn directly on the geometry. This
approach provides a more direct and intuitive user experience for designers. We
visualize our adjoint gradients and compare them to image-based
state-of-the-art differentiable rendering methods. We also compare the
convergence behavior of various optimization algorithms when using our gradient
data vs. image-based differentiable rendering methods. Qualitative comparisons
with real-world scenes underline the practical applicability of our method.

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