QSplat: a multiresolution point rendering system for large meshes
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Hardware-accelerated point-based rendering of complex scenes
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
POP: a hybrid point and polygon rendering system for large data
Proceedings of the conference on Visualization '01
ACM SIGGRAPH 2003 Papers
High-Quality Point-Based Rendering on Modern GPUs
PG '03 Proceedings of the 11th Pacific Conference on Computer Graphics and Applications
Perspective accurate splatting
GI '04 Proceedings of the 2004 Graphics Interface Conference
A geoscience perspective on immersive 3D gridded data visualization
Computers & Geosciences
Immersive Visualization and Analysis of LiDAR Data
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Point-based rendering techniques
Computers and Graphics
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
High-quality surface splatting on today's GPUs
SPBG'05 Proceedings of the Second Eurographics / IEEE VGTC conference on Point-Based Graphics
Visually-complete aerial LiDAR point cloud rendering
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Fusing oblique imagery with augmented aerial LiDAR
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
Hi-index | 0.00 |
Remote sensing technologies, such as LIDAR, rapidly evolve and produce large datasets. The computers used to visualize these data have limited resources, which prevent detailed and real-time visualization. An approach to real-time visualization of virtually unlimited LIDAR datasets, at full detail with a hierarchical and out-of-core approach to data management and a modern point-based rendering technique, is presented. It is based on on-demand loading of data subsets into their optimal memory locations and on a two-pass point-based rendering method that utilizes elliptical weighted average filtering to reduce alias. In addition, points are rotated in accordance to their distance and orientation from the viewer. All graphics computations are implemented in programmable shaders on the GPU, so the CPU is free to perform other tasks. The capability of our approach is compared with the Kreylos et al. (2008) method.