3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes (2407.07090v3)

Abstract: Particle-based representations of radiance fields such as 3D Gaussian Splatting have found great success for reconstructing and re-rendering of complex scenes. Most existing methods render particles via rasterization, projecting them to screen space tiles for processing in a sorted order. This work instead considers ray tracing the particles, building a bounding volume hierarchy and casting a ray for each pixel using high-performance GPU ray tracing hardware. To efficiently handle large numbers of semi-transparent particles, we describe a specialized rendering algorithm which encapsulates particles with bounding meshes to leverage fast ray-triangle intersections, and shades batches of intersections in depth-order. The benefits of ray tracing are well-known in computer graphics: processing incoherent rays for secondary lighting effects such as shadows and reflections, rendering from highly-distorted cameras common in robotics, stochastically sampling rays, and more. With our renderer, this flexibility comes at little cost compared to rasterization. Experiments demonstrate the speed and accuracy of our approach, as well as several applications in computer graphics and vision. We further propose related improvements to the basic Gaussian representation, including a simple use of generalized kernel functions which significantly reduces particle hit counts.

• The paper presents an efficient ray tracing method using 3D Gaussian splats to accelerate rendering of particle-based radiance fields.
• It builds a tailored BVH with stretched icosahedrons for fast ray-triangle intersections and enables differentiable rendering for optimization.
• Experimental benchmarks demonstrate competitive rendering times and superior image quality metrics compared to state-of-the-art approaches.

3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes

Introduction

The paper "3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes" explores an efficient algorithm for ray tracing particle-based representations of radiance fields. Unlike traditional methods that leverage rasterization for rendering particles, this research adopts a ray tracing approach which enables the processing of incoherent rays for advanced lighting effects and high-distortion cameras. The motivation stems from the limitations inherent to rasterization, particularly in handling secondary rays and distorted camera models central to applications in robotics, AR/VR, and complex scene rendering.

Ray Tracing vs. Rasterization

Rendering methods typically oscillate between rasterization for real-time applications and ray tracing for high-fidelity offline rendering. Specialized GPU hardware has pushed ray tracing towards real-time performance, offering flexibility at a comparable cost to rasterization. This paper's aim is to harness the benefits of ray tracing for particle scenes, specifically those represented by 3D Gaussian splats, without the usual performance drawbacks in various rendering contexts.

Methodology

Key innovations in this work include building a Bounding Volume Hierarchy (BVH) and using high-performance GPU ray tracing hardware to optimize the rendering of particle scenes. This method involves a tailored algorithm that encapsulates particles within bounding meshes, facilitating fast ray-triangle intersections and efficient shading in depth-order.

Core Components

1. Bounding Primitives:
   • The paper discusses various bounding primitives including axis-aligned bounding boxes (AABBs), octahedrons, and icosahedrons. The chosen approach uses a stretched regular icosahedron, transformed to cover particle spaces with a specified minimum response, leading to better performance.
2. Ray Tracing Renderer:
   • The proposed renderer casts rays against the BVH to gather particle hits, processes these hits in sorted order, and evaluates contributions until sufficient opacity is achieved. This approach is compared against naive closest-hit tracing and methods from prior work, such as slab tracing and multilayer alpha tracing.
3. Differentiable Rendering:
   • Building on ray tracing, the renderer is designed to facilitate optimization through differentiation of the ray tracing process with respect to particle parameters. This enables gradient-based optimization for scene reconstruction from observed data.
4. Generalized Particle Kernels:
   • Besides standard Gaussian kernels, the paper explores generalized Gaussians, kernelized surfaces, and cosine wave modulations to provide efficient alternatives that reduce the number of intersections and improve rendering performance.

Results and Benchmarks

The implementation and experiments demonstrate the method's efficacy in terms of both speed and quality across various benchmarks, including MipNeRF360, Tanks and Temples, and Deep Blending datasets. Notably, the ray tracing approach achieves competitive rendering times and superior image quality metrics such as PSNR and SSIM when compared to state-of-the-art methods like 3D Gaussian Splatting (3DGS), Instant Neural Graphics Primitives (INGP), and MipNeRF360.

Applications and Implications

The proposed renderer opens numerous promising avenues in the domain of computer graphics and vision:

1. Ray-Based Effects:
   • Capabilities such as reflections, refractions, inserted geometry, depth of field, and artificial shadows are seamlessly integrated, demonstrating the flexibility of ray tracing over rasterization.
2. Complex Camera Models:
   • The method naturally accommodates diverse camera models including highly distorted fisheye lenses and rolling shutter cameras, which are critical for accurate simulations in robotics and autonomous driving.
3. Stochastic Sampling and Denoising:
   • The flexibility of ray tracing allows stochastic ray sampling, significantly aiding in training scenarios where efficient subset sampling is required.
4. Instancing:
   • Efficient handling of multiple instances of objects demonstrates the powerful geometric instancing of particle scenes without duplicating geometry, maintaining real-time performance.

Future Work and Conclusion

This research establishes a foundational technique enabling efficient ray-traced rendering of particle scenes, facilitating further work on inverse lighting, global illumination, and other advanced effects in particle-based representations. Despite the slower performance compared to rasterization for pinhole camera rendering, the proposed method’s comprehensive applicability and maintainability for various tasks underscore its significance.

In conclusion, "3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes" brings forth substantial advancements in rendering particle-based radiance fields using ray tracing, providing new tools and methods to foster further research and development in the fields of computer graphics and vision.