Octree-based Point-Cloud Compression

Files

111-120.pdf (325.91 KB)

Date

2006

Authors

Schnabel, Ruwen
Klein, Reinhard

Publisher

The Eurographics Association

Abstract

In this paper we present a progressive compression method for point sampled models that is specifically apt at dealing with densely sampled surface geometry. The compression is lossless and therefore is also suitable for storing the unfiltered, raw scan data. Our method is based on an octree decomposition of space. The point-cloud is encoded in terms of occupied octree-cells. To compress the octree we employ novel prediction techniques that were specifically designed for point sampled geometry and are based on local surface approximations to achieve high compression rates that outperform previous progressive coders for point-sampled geometry. Moreover we demonstrate that additional point attributes, such as color, which are of great importance for point-sampled geometry, can be well integrated and efficiently encoded in this framework.

        @inproceedings{:10.2312/SPBG/SPBG06/111-120
,
booktitle = {Symposium on Point-Based Graphics
},
editor = {Mario Botsch and Baoquan Chen and Mark Pauly and Matthias Zwicker
},
title = {{Octree-based Point-Cloud Compression
}},
author = {Schnabel, Ruwen and 
Klein, Reinhard
},
year = {2006
},
publisher = {The Eurographics Association
},
ISSN = {1811-7813
},
ISBN = {3-905673-32-0
},
DOI = {/10.2312/SPBG/SPBG06/111-120
}
}