Open Access
Peer-Reviewed
Original Research
Smooth Visualization of Large Point Clouds
Abstract
We present a novel approach for processing and rendering large point cloud data from 3D scanners on a standard computer system. Our technique handles a data size that typically exceeds the RAM for processing and the VRAM for rendering the data . We achieve interactive framerates and a smooth visualization by enhancing existing large data visualization techniques, like Level of Detail and deferred rendering approaches and we utilize the new capabilities of modern GPU hardware. This enables the exploration of large and unstructured 3d scan data sets whose size is only limited by the hard disk memory available. We verify our approach at the example of different data sets with up to one billion 3D points.
Keywords
3D Point clouds
Out-of-core
Level of Detail
Deferred rendering
Interactive visualization
Declarations & Ethics
Funding:
This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest:
The authors declare no competing financial or institutional interests.
Peer Review:
Double-blind peer reviewed by international subject specialists.
License:
Creative Commons Attribution 4.0 International (CC BY 4.0).
How to Cite This Article
APA / MLA / BibTeX
Futterlieb, et al. (2016). Smooth Visualization of Large Point Clouds. IADIS International Journal on Computer Science and Information Systems, 11(2). https://doi.org/10.33965/ijcsis_2016_v11i2_12
Futterlieb, et al. "Smooth Visualization of Large Point Clouds." IADIS International Journal on Computer Science and Information Systems, vol. 11, no. 2, 2016. https://doi.org/10.33965/ijcsis_2016_v11i2_12
Futterlieb, et al. "Smooth Visualization of Large Point Clouds." IADIS International Journal on Computer Science and Information Systems 11, no. 2 (2016). https://doi.org/10.33965/ijcsis_2016_v11i2_12