Comparison of Modern Omnidirectional Precise Shadowing Techniques Versus Ray Tracing

Abstract

This paper presents an in depth comparison of state‐of‐the‐art precise shadowing techniques for an omnidirectional point light. We chose several types of modern shadowing algorithms, starting from stencil shadow volumes, methods using traversal of acceleration structures to hardware‐accelerated ray‐traced shadows. Some methods were further improved – robustness, increased performance; we also provide the first multi‐platform implementations of some of the tested algorithms. All the methods are evaluated on several test scenes in different resolutions and on two hardware platforms – with and without dedicated hardware units for ray tracing. We conclude our findings based on speed and memory consumption. Ray‐tracing is the fastest and one of the easiest methods to implement with small memory footprint. The Omnidirectional Frustum‐Traced Shadows method has a predictable memory footprint and is the second fastest algorithm tested. Our stencil shadow volumes are faster than some newer algorithms. Per‐Triangle Shadow Volumes and Clustered Per‐Triangle Shadow Volumes are difficult to implement and require the most memory; the latter method scales well with the scene complexity and resolution. Deep Partitioned Shadow Volumes does not excel in any of the measured parameters and is suitable for smaller scenes. The source codes of the testing framework have been made publicly available.

Efficient Simulation of Light Scattering Effects in the Atmosphere

“…To accurately mimic these visual effects, researchers and developers have employed a variety of scattering models that approximate the true scattering behavior. Some widely used theoretical models and methods include: Rayleigh scattering [5], Mie Scattering [6], Henyey-Greenstein Phase Function [7], Monte Carlo Method [8], Light scattering integrals in ray tracing algorithms [9] and so on. Each model and method have its own range of applicability and trade-offs, and the choice often depends on the desired level of accuracy, computational resources, and specific application scenarios.…”