On sparse voxel DAGs and memory efficient compression of surface attributes for real-time scenarios
Doktorsavhandling, 2022

The general shape of a 3D object can expeditiously be represented as, e.g., triangles or voxels, while smaller-scale features usually are parameterized over the surface of the object. Such features include, but are not limited to, color details, small-scale surface-normal variations, or even view-dependent properties required for the light-surface interactions. This thesis is a collection of four papers that focus on new ways to compress and efficiently utilize surface data in 3D for real-time usage.
In Paper IA and IB, we extend upon the concept of sparse voxel DAGs, a real-time compression format of a voxel-grid, to allow an attribute mapping with a negligible impact on the size. The main contribution, however, is a novel real-time compression format of the mapped colors over such sparse voxel surfaces.
Paper II aims to utilize the results of the previous papers to achieve uv-free texturing of surfaces, such as triangle meshes, with optimized run-time minification as well as magnification filtering.
Paper III extends upon previous compact representations of view dependent radiance using spherical gaussians (SG). By using a convolutional neural network, we are able to compress the light-field by finding SGs with free directions, amplitudes and sharpnesses, whereas previous methods were limited to only free amplitudes in similar scenarios.

directed acyclic graph

surface properties

neural networks



spherical gaussians

light field




Opponent: Associate Professor Cem Yuksel, School of Computing, University of Utah, USA


Dan Dolonius

Chalmers, Data- och informationsteknik, Datorteknik

Spherical Gaussian Light‐field Textures for Fast Precomputed Global Illumination

Computer Graphics Forum,; Vol. 39(2020)p. 133-146

Artikel i vetenskaplig tidskrift

UV-free Texturing using Sparse Voxel DAGs

Computer Graphics Forum,; Vol. 39(2020)p. 121-132

Artikel i vetenskaplig tidskrift

Compressing color data for voxelized surface geometry

IEEE Transactions on Visualization and Computer Graphics,; Vol. 25(2019)p. 1270-1282

Artikel i vetenskaplig tidskrift

Compressing color data for voxelized surface geometry

Proceedings of the 21st ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games,; (2017)p. 13:1--13:10-

Paper i proceeding

In computer graphics, the general shape of a 3D object is commonly composed of larger building blocks (primitives) such as voxels or triangles. By adding properties, such as colors and small-scale surface-normal variations, we can approximate how light will scatter and be absorbed, in order to render more physically plausible images. However, since such details need to be of much higher frequency than the geometry, it becomes infeasible to store such information on a per primitive basis, and thus they are generally stored in other forms, such as images, and are then mapped to the geometry during rendering. In order to speed up calculations, it is also not uncommon to precompute certain view-dependent properties for light-surface interactions, at the expense of memory overhead.

This thesis aims to improve and extend existing representations in order
to decrease the memory footprint while still being inexpensive to visualize
with high quality.


Datavetenskap (datalogi)



Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5097





Opponent: Associate Professor Cem Yuksel, School of Computing, University of Utah, USA

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