Fast Voxelization and Level of Detail for Microgeometry Rendering
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866918447039905792 |
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| author | Fabre, Javier Castillo, Carlos Rodriguez-Pardo, Carlos Lopez-Moreno, Jorge |
| author_facet | Fabre, Javier Castillo, Carlos Rodriguez-Pardo, Carlos Lopez-Moreno, Jorge |
| contents | Many materials show anisotropic light scattering patterns due to the shape and local alignment of their underlying micro structures: surfaces with small elements such as fibers, or the ridges of a brushed metal, are very sparse and require a high spatial resolution to be properly represented as a volume. The acquisition of voxel data from such objects is a time and memory-intensive task, and most rendering approaches require an additional Level-of-Detail (LoD) data structure to aggregate the visual appearance, as observed from multiple distances, in order to reduce the number of samples computed per pixel (E.g.: MIP mapping). In this work we introduce first, an efficient parallel voxelization method designed to facilitate fast data aggregation at multiple resolution levels, and second, a novel representation based on hierarchical SGGX clustering that provides better accuracy than baseline methods. We validate our approach with a CUDA-based implementation of the voxelizer, tested both on triangle meshes and volumetric fabrics modeled with explicit fibers. Finally, we show the results generated with a path tracer based on the proposed LoD rendering model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_13191 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Fast Voxelization and Level of Detail for Microgeometry Rendering Fabre, Javier Castillo, Carlos Rodriguez-Pardo, Carlos Lopez-Moreno, Jorge Graphics Machine Learning I.3.7; I.3.5; I.3.2 Many materials show anisotropic light scattering patterns due to the shape and local alignment of their underlying micro structures: surfaces with small elements such as fibers, or the ridges of a brushed metal, are very sparse and require a high spatial resolution to be properly represented as a volume. The acquisition of voxel data from such objects is a time and memory-intensive task, and most rendering approaches require an additional Level-of-Detail (LoD) data structure to aggregate the visual appearance, as observed from multiple distances, in order to reduce the number of samples computed per pixel (E.g.: MIP mapping). In this work we introduce first, an efficient parallel voxelization method designed to facilitate fast data aggregation at multiple resolution levels, and second, a novel representation based on hierarchical SGGX clustering that provides better accuracy than baseline methods. We validate our approach with a CUDA-based implementation of the voxelizer, tested both on triangle meshes and volumetric fabrics modeled with explicit fibers. Finally, we show the results generated with a path tracer based on the proposed LoD rendering model. |
| title | Fast Voxelization and Level of Detail for Microgeometry Rendering |
| topic | Graphics Machine Learning I.3.7; I.3.5; I.3.2 |
| url | https://arxiv.org/abs/2604.13191 |