Geometry and Attribute Compression for Voxel Scenes

Journal article (2016)

Authors

B Dado

T.R. Kol Computer Graphics and Visualisation -

P. Bauszat Computer Graphics and Visualisation -

J.M.C.M. Thiery Computer Graphics and Visualisation -

E. Eisemann Computer Graphics and Visualisation -

Research Group

Computer Graphics and Visualisation () (TU Delft)

More Info

expand_more

To reference this document use:

http://resolver.tudelft.nl/uuid:1e841d2f-3e6c-4af9-b40f-f0871bbc5efb

Published Date

2016

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Computer Graphics and Visualisation

Abstract

Voxel-based approaches are today's standard to encode volume data. Recently, directed acyclic graphs (DAGs) were successfully used for compressing sparse voxel scenes as well, but they are restricted to a single bit of (geometry) information per voxel. We present a method to compress arbitrary data, such as colors, normals, or reflectance information. By decoupling geometry and voxel data via a novel mapping scheme, we are able to apply the DAG principle to encode the topology, while using a palette-based compression for the voxel attributes, leading to a drastic memory reduction. Our method outperforms existing state-of-the-art techniques and is well-suited for GPU architectures. We achieve real-time performance on commodity hardware for colored scenes with up to 17 hierarchical levels (a 128K3voxel resolution), which are stored fully in core.