Geometry and Attribute Compression for Voxel Scenes

B Dado, Timothy R. Kol, Pablo Bauszat, Jean-Marc Thiery, Elmar Eisemann

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)397-407
Number of pages11
JournalComputer Graphics Forum (online)
Volume35
Issue number2
DOIs
Publication statusPublished - 2016
EventEurographics 2016: The 37th Annual Conference of the European Association for Computer Graphics - Lisbon, Portugal
Duration: 9 May 201613 May 2016

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