Self-Similarity-Based Compression of Point Clouds, with Application to Ray Tracing
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Date
2007
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Many real-world, scanned surfaces contain repetitive structures, like bumps, ridges, creases, and so on.We present a compression technique that exploits self-similarity within a point-sampled surface. Our method replaces similar surface patches with an instance of a representative patch. We use a concise shape descriptor to identify and cluster similar patches. Decoding is achieved through simple instancing of the representative patches. Encoding is efficient, and can be applied to large datasets consisting of millions of points. Moreover, our technique offers random access to the compressed data, making it applicable to ray tracing, and easily allows for storing additional point attributes, like normals.
Description
@inproceedings{:10.2312/SPBG/SPBG07/129-137,
booktitle = {Eurographics Symposium on Point-Based Graphics},
editor = {M. Botsch and R. Pajarola and B. Chen and M. Zwicker},
title = {{Self-Similarity-Based Compression of Point Clouds, with Application to Ray Tracing}},
author = {Hubo, Erik and Mertens, Tom and Haber, Tom and Bekaert, Philippe},
year = {2007},
publisher = {The Eurographics Association},
ISSN = {1811-7813},
ISBN = {978-3-905673-51-7},
DOI = {/10.2312/SPBG/SPBG07/129-137}
}