Compression of Voxel Models

Abstract

This website contains the documentation of my research project at TU Dresden. The goal of the project is to develop an efficient algorithm for compressing voxel models. As an input format, an unsorted list of 3D integer coordinates and attribute data is used. Multiple methods for encoding geometry data including Cuboid Extraction (CE), Sparse Voxel Octrees (SVOs) with Space-Filling Curves, and Run-Length Encoding (RLE) are explained and then compared in terms of complexity, compression ratio, and real life performance. CE fails based on its high complexity, SVOs and RLE perform almost identically in terms of compression ratio and complexity. SVOs are the clear winner because of their lower real life memory requirements when reading the input data, resulting in better performance.

The Free Lossless Voxel Compression (FLVC) codec is developed based on these findings. Its advantages include arbitrary attribute information per voxel, high performance, streamability, and very low memory requirements for decoding. The codec is made available through a FOSS command-line utility which can convert between various common voxel model formats and the new FLVC format.

Relevant Links

• FLVC Command-Line Interface
• This documentation on GitHub

Notes