Title: | Anisotropic octrees: a tool for fast normals estimation on unorganized point clouds |
Authors: | Ravaglia, Joris Bac, Alexandra Fournier, Richard A. |
Citation: | WSCG '2017: short communications proceedings: The 25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2016 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech RepublicMay 29 - June 2 2017, p. 101-110. |
Issue Date: | 2017 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | wscg.zcu.cz/WSCG2017/!!_CSRN-2702.pdf http://hdl.handle.net/11025/29740 |
ISBN: | 978-80-86943-45-9 |
ISSN: | 2464-4617 |
Keywords: | bodová mračna;zakřivení;oktáva;anizotropie;kvadratická plocha |
Keywords in different language: | point clouds;curvature;octree;anisotropy;quadratic surface |
Abstract: | With the recent advances in remote sensing of objects and environments, point cloud processing has become a major field of study. Three-dimensional point cloud collected with remote sensing instruments may be very large, containing up to several tens of billions of points. This imposes the use for efficient and automatic algorithms to extract geometric or structural elements of the scanned surfaces. In this paper, we focus on the estimation of normal directions in an unorganized point cloud and provide a curvature indicator. We avoid point-wise operations to accelerate the running time for normals estimation. Instead, our method rely on an innovative anisotropic partitioning of the point cloud using an octree structure guided by the geometric complexity of the data and generates patches of points. These patches are then approximated by a quadratic surface in order to estimate the normal directions and curvatures. Our method has been applied to six models of various types presenting different characteristics and performs, in average, 2.65 times faster than multi-threads implementations available in current pieces of software. The results obtained are a compromise between running time efficiency and normals accuracy. Moreover, this work opens up promising perspectives and can be easily inserted in wide range of workflows. |
Rights: | © Václav Skala - UNION Agency |
Appears in Collections: | WSCG '2017: Short Papers Proceedings |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Ravaglia.pdf | Plný text | 5,37 MB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/29740
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.