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Interactive Visualization of Large Point Clouds Using an Autotuning Multiresolution Out-Of-Core Strategy
dc.contributor.author | Teijeiro, Diego | |
dc.contributor.author | Amor, Margarita | |
dc.contributor.author | Doallo, Ramón | |
dc.contributor.author | Deibe, David | |
dc.date.accessioned | 2023-11-20T14:10:19Z | |
dc.date.available | 2023-11-20T14:10:19Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | D. Teijeiro, M. Amor, R. Doallo, and D. Deibe, "Interactive Visualization of Large Point Clouds Using an Autotuning Multiresolution Out-Of-Core Strategy", The Computer Journal, Vol. 66, Issue 7, July 2023, P. 1802–1816, doi: https://doi.org/10.1093/comjnl/bxac179 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/34298 | |
dc.description | Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG | es_ES |
dc.description.abstract | [Abstract]: Due to the increasingly large amount of data acquired into point clouds, from LiDAR (Light Detection and Ranging) sensors and 2D/3D sensors, massive point clouds processing has become a topic with high interest for several fields. Current client-server applications usually use multiresolution out-of-core proposals; nevertheless, the construction of the data structures required is very time-consuming. Furthermore, these multiresolution approaches present problems regarding point density changes between different levels of detail and artifacts due to the rendering of elements entering and leaving the field of view. We present an autotuning multiresolution out-of-core strategy to avoid these problems. Other objectives are reducing loading times while maintaining low memory requirements, high visualization quality and achieving interactive visualization of massive point clouds. This strategy identifies certain parameters, called performance parameters, and defines a set of premises to obtain the goals mentioned above. The optimal parameter values depend on the number of points per cell in the multiresolution structure. We test our proposal in our web-based visualization software designed to work with the structures and storage format used and display massive point clouds achieving interactive visualization of point clouds with more than 27 billion points. | es_ES |
dc.description.sponsorship | Ministry of Science and Innovation of Spain (PID2019-104184RB-I00 / AEI / 10.13039/501100011033); Galician Government under the Consolidation Program of Competitive Research Units (Ref. ED431C 2021/30); Centro de Investigación de Galicia ”CITIC”; Government of Galicia; European Union (European Regional Development Fund- Galicia 2014-2020 Program by grant ED431G 2019/01); Government of Galicia and the European Social Fund (ESF) of the European Union (predoctoral fellowship ref. ED481A-2019/231 to D.T.); Funding for open access charge: Universidade da Coruña/CISUG. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2021/30 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED481A-2019/231 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Oxford University Press | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104184RB-I00/ES/DESAFIOS ACTUALES EN HPC: ARQUITECTURAS, SOFTWARE Y APLICACIONES/ | es_ES |
dc.relation.uri | https://doi.org/10.1093/comjnl/bxac179 | es_ES |
dc.rights | Atribución-NoComercial-CompartirIgual 4.0 (International) | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/es/ | * |
dc.subject | efficient data structures | es_ES |
dc.subject | LiDAR | es_ES |
dc.subject | multiresolution | es_ES |
dc.subject | out-of-core strategy | es_ES |
dc.subject | web-visualization | es_ES |
dc.title | Interactive Visualization of Large Point Clouds Using an Autotuning Multiresolution Out-Of-Core Strategy | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | The Computer Journal | es_ES |
UDC.volume | 66 | es_ES |
UDC.issue | 7 | es_ES |
UDC.startPage | 1802 | es_ES |
UDC.endPage | 1816 | es_ES |
dc.identifier.doi | 10.1093/comjnl/bxac179 |
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