QSplat: a multiresolution point rendering system for large meshes
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Proceedings of the conference on Visualization '01
Instant points: fast rendering of unprocessed point clouds
SPBG'06 Proceedings of the 3rd Eurographics / IEEE VGTC conference on Point-Based Graphics
Visualization of LIDAR datasets using point-based rendering technique
Computers & Geosciences
Graphics for Serious Games: VFire: Immersive wildfire simulation and visualization
Computers and Graphics
Immersive out-of-core visualization of large-size and long-timescale molecular dynamics trajectories
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Immersive visualization and interactive analysis of ground penetrating radar data
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Visually-complete aerial LiDAR point cloud rendering
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Point-based rendering optimization with textured meshes for fast LiDAR visualization
Computers & Geosciences
Process virtualization of large-scale lidar data in a cloud computing environment
Computers & Geosciences
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We describe an immersive visualization application for point cloud data gathered by LiDAR (Light Detection And Ranging) scanners. LiDAR is used by geophysicists and engineers to make highly accurate measurements of the landscape for study of natural hazards such as floods and earthquakes. The large point cloud data sets provided by LiDAR scans create a significant technical challenge for visualizing, assessing, and interpreting these data. Our system uses an out-of-core view-dependent multiresolution rendering scheme that supports rendering of data sets containing billions of 3D points at the frame rates required for immersion (48---60 fps). The visualization system is the foundation for several interactive analysis tools for quality control, extraction of survey measurements, and the extraction of isolated point cloud features. The software is used extensively by researchers at the UC Davis Department of Geology and the U.S. Geological Survey, who report that it offers several significant advantages over other analysis methods for the same type of data, especially when used in an immersive visualization environment such as a CAVE.