The Compression Method of Point Cloud Data based on the Hypotenuse-height Deviation Method

DOI

10.2991/wartia-16.2016.364How to use a DOI?

Keywords

point cloud compression, hierarchy, hypotenuse-height difference, linear feature, plan curvature

Abstract

The article describes a hypotenuse-height deviation compression method of magnanimous point cloud data based on hierarchy. Firstly the point cloud is stratified into several hierarchies which turn into linear point clouds, then compressed by using hypotenuse-height deviation threshold. By experiment, the compression effect of the method brought up is compared with that of several traditional point cloud compression methods, which verify the capability of realizing high-efficiency compression with abundant detailed features retained.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chenghui Wan
AU  - Xiping He
PY  - 2016/05
DA  - 2016/05
TI  - The Compression Method of Point Cloud Data based on the Hypotenuse-height Deviation Method
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1835
EP  - 1838
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.364
DO  - 10.2991/wartia-16.2016.364
ID  - Wan2016/05
ER  -