Open Source First Person View 3D Point Cloud Visualizer for Large Data Sets
| Autor: | Palha, Arnaud, Murtiyoso, Arnadi, Michelin, Jean-Christophe, Alby, Emmanuel, Grussenmeyer, Pierre, Ivan, Igor, Singleton, Alex, Horák, Jiří, Inspektor, Tomáš |
|---|---|
| Přispěvatelé: | Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
[SPI.OTHER]Engineering Sciences [physics]/Other
Source code Laser scanning Computer science media_common.quotation_subject OpenGL Immersive Point cloud 02 engineering and technology 010502 geochemistry & geophysics computer.software_genre 01 natural sciences Rendering (computer graphics) Software Computer graphics (images) 0202 electrical engineering electronic engineering information engineering Quadtree Random tree sampling 0105 earth and related environmental sciences media_common Visualization Database business.industry 020207 software engineering Large point cloud business computer |
| Zdroj: | The Rise of Big Spatial Data The Rise of Big Spatial Data, Springer, pp.27-39, 2016, Lecture Notes in Geoinformation and Cartography, 978-3-319-45122-0. ⟨10.1007/978-3-319-45123-7_3⟩ Lecture Notes in Geoinformation and Cartography ISBN: 9783319451220 |
| DOI: | 10.1007/978-3-319-45123-7_3⟩ |
| Popis: | International audience; The use of laser scanning techniques has become a common way to measure the real world. Millions of points could be generated by this system, which brings forth the problem of visualizing and eventually performing analyses on them. In the open source domain, various software packages exist to visualize 3D point clouds. However, most of these software packages do not allow the real-time rendering of large point clouds. Few of them also allow visualization in an immersive manner. The research aims to create an open source viewer for large 3D point clouds, which enables a dynamic and immersive visualization. In order to do so, rendering and point cloud management strategies must be implemented to avoid overloading the computer’s memory. The rendering is done using OpenGL engine by utilizing the graphic card’s memory in order to perform faster visualization. The program consists of a pre-processing stage in which the point cloud files are divided into quadtrees and then subsampled using the random tree sampling method. The visualization itself will calculate the distance between the point of view and the center of nodes generated by the pre-processing stage. The amount of points rendered within each node will depend on this distance; the farther away the node is from the point of view, the fewer points are rendered. A loading and unloading function enables the point cloud to be rendered dynamically. With the point cloud management algorithm implemented, the resulting program is able to load large point clouds generated by a mobile laser scanner using an ordinary computer. The resulting program as well as the source code will be available for the public due to its open source nature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|