View-Independent Adjoint Light Tracing for Lighting Design Optimization

Information

• Publication Type: Journal Paper with Conference Talk
• Workgroup(s)/Project(s):
  • Advanced Computational Design
• Date: May 2024
• Journal: ACM Transactions on Graphics
• Volume: 43
• Open Access: yes
• Number: 3
• Article Number: 35
• ISSN: 1557-7368
• Event: SIGGRAPH 2024
• DOI: 10.1145/3662180
• Pages: 16
• Publisher: ASSOC COMPUTING MACHINERY
• Keywords: differentiable rendering, global illumination, Lighting design, optimization, ray tracing

Abstract

Differentiable rendering methods promise the ability to optimize various parameters of three-dimensional (3D) scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this article, we introduce a method that enables continuous optimization of the arrangement of luminaires in a 3D scene via differentiable light tracing. Our experiments show two major issues when attempting to apply existing methods from differentiable path tracing to this problem: First, many rendering methods produce images, which restricts the ability of a designer to define lighting objectives to image space. Second, most previous methods are designed for scene geometry or material optimization and have not been extensively tested for the case of optimizing light sources. Currently available differentiable ray-tracing methods do not provide satisfactory performance, even on fairly basic test cases in our experience. In this article, we propose, to the best of our knowledge, a novel adjoint light tracing method that overcomes these challenges and enables gradient-based lighting design optimization in a view-independent (camera-free) way. Thus, we allow the user to paint illumination targets directly onto the 3D scene or use existing baked illumination data (e.g., light maps). Using modern ray-tracing hardware, we achieve interactive performance. We find light tracing advantageous over path tracing in this setting, as it naturally handles irregular geometry, resulting in less noise and improved optimization convergence. We compare our adjoint gradients to state-of-the-art image-based differentiable rendering methods. We also demonstrate that our gradient data works with various common optimization algorithms, providing good convergence behaviour. Qualitative comparisons with real-world scenes underline the practical applicability of our method.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1145/3662180

BibTeX

@article{lipp-2024-val,
  title =      "View-Independent Adjoint Light Tracing for Lighting Design
               Optimization",
  author =     "Lukas Lipp and David Hahn and Pierre Ecormier-Nocca and
               Florian Rist and Michael Wimmer",
  year =       "2024",
  abstract =   "Differentiable rendering methods promise the ability to
               optimize various parameters of three-dimensional (3D) scenes
               to achieve a desired result. However, lighting design has so
               far received little attention in this field. In this
               article, we introduce a method that enables continuous
               optimization of the arrangement of luminaires in a 3D scene
               via differentiable light tracing. Our experiments show two
               major issues when attempting to apply existing methods from
               differentiable path tracing to this problem: First, many
               rendering methods produce images, which restricts the
               ability of a designer to define lighting objectives to image
               space. Second, most previous methods are designed for scene
               geometry or material optimization and have not been
               extensively tested for the case of optimizing light sources.
               Currently available differentiable ray-tracing methods do
               not provide satisfactory performance, even on fairly basic
               test cases in our experience. In this article, we propose,
               to the best of our knowledge, a novel adjoint light tracing
               method that overcomes these challenges and enables
               gradient-based lighting design optimization in a
               view-independent (camera-free) way. Thus, we allow the user
               to paint illumination targets directly onto the 3D scene or
               use existing baked illumination data (e.g., light maps).
               Using modern ray-tracing hardware, we achieve interactive
               performance. We find light tracing advantageous over path
               tracing in this setting, as it naturally handles irregular
               geometry, resulting in less noise and improved optimization
               convergence. We compare our adjoint gradients to
               state-of-the-art image-based differentiable rendering
               methods. We also demonstrate that our gradient data works
               with various common optimization algorithms, providing good
               convergence behaviour. Qualitative comparisons with
               real-world scenes underline the practical applicability of
               our method.",
  month =      may,
  journal =    "ACM Transactions on Graphics",
  volume =     "43",
  number =     "3",
  articleno =  "35",
  issn =       "1557-7368",
  doi =        "10.1145/3662180",
  pages =      "16",
  publisher =  "ASSOC COMPUTING MACHINERY",
  keywords =   "differentiable rendering, global illumination, Lighting
               design, optimization, ray tracing",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2024/lipp-2024-val/",
}