Self-Similarity-Based Compression of Point Clouds, with Application to Ray Tracing
dc.contributor.author | Hubo, Erik | en_US |
dc.contributor.author | Mertens, Tom | en_US |
dc.contributor.author | Haber, Tom | en_US |
dc.contributor.author | Bekaert, Philippe | en_US |
dc.contributor.editor | M. Botsch and R. Pajarola and B. Chen and M. Zwicker | en_US |
dc.date.accessioned | 2014-01-29T16:52:13Z | |
dc.date.available | 2014-01-29T16:52:13Z | |
dc.date.issued | 2007 | en_US |
dc.description.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. | en_US |
dc.description.seriesinformation | Eurographics Symposium on Point-Based Graphics | en_US |
dc.identifier.isbn | 978-3-905673-51-7 | en_US |
dc.identifier.issn | 1811-7813 | en_US |
dc.identifier.uri | https://doi.org/10.2312/SPBG/SPBG07/129-137 | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational geometry and object modeling - Curve, surface, solid and object representations; E.4 [Data]: Coding and information theory - Data compaction and compression | en_US |
dc.title | Self-Similarity-Based Compression of Point Clouds, with Application to Ray Tracing | en_US |