首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Supporting multi-resolution out-of-core rendering of massive LiDAR point clouds through non-redundant data structures
Authors:David Deibe  Margarita Amor  Ramón Doallo
Institution:Faculty of Computer Science, University of A Coru?a (UDC), A Coru?a, Spain
Abstract:In recent years, the evolution and improvement of LiDAR (Light Detection and Ranging) hardware has increased the quality and quantity of the gathered data, making the storage, processing and management thereof particularly challenging. In this work we present a novel, multi-resolution, out-of-core technique, used for web-based visualization and implemented through a non-redundant, data point organization method, which we call Hierarchically Layered Tiles (HLT), and a tree-like structure called Tile Grid Partitioning Tree (TGPT). The design of these elements is mainly focused on attaining very low levels of memory consumption, disk storage usage and network traffic on both, client and server-side, while delivering high-performance interactive visualization of massive LiDAR point clouds (up to 28 billion points) on multiplatform environments (mobile devices or desktop computers). HLT and TGPT were incorporated and tested in ViLMA (Visualization for LiDAR data using a Multi-resolution Approach), our own web-based visualization software specially designed to work with massive LiDAR point clouds.
Keywords:LiDAR  web-visualization  efficient data structures  multi-resolution  out-of-core
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号