Title
Improving Transparent Visualization of Large-Scale Laser-Scanned Point Clouds by Using Poisson Disk Sampling
Abstract
In recent years, due to the development of laser-measurement technology, 3D laser-scanned point clouds for cultural assets are often used as the recording format of digital archiving. The acquired point clouds are large-scale and precisely record complex 3D internal structures of the scanned objects. Visualization quality of such point clouds highly depends on density distributional uniformity, that is, the uniformity of the inter-point distances. The visualization quality can be improved by making point distances uniform. In addition, the visibility further improves by emphasizing edges. In this study, first the uniformity and flexible tuning of the point density based on Poisson disk sampling are examined. The resultant high-quality point clouds are then applied to transparent visualization. Moreover, edge emphasis visualization is realized by combining the principal component analysis calculating feature amount and Poisson disk sampling.
Year
DOI
Venue
2017
10.1109/Culture.and.Computing.2017.19
2017 International Conference on Culture and Computing (Culture and Computing)
Keywords
Field
DocType
laser-scanned point cloud,transparent visualization,feature-highlighting visualization,principal component analysis,curvature,poisson disk sampling
Data visualization,Visibility,Computer graphics (images),Visualization,Computer science,Laser,Poisson disk sampling,Recording format,Point cloud,Principal component analysis
Conference
ISBN
Citations 
PageRank 
978-1-5386-1136-4
0
0.34
References 
Authors
5
6
Name
Order
Citations
PageRank
Shu Yanai100.34
Ryohei Umegaki200.34
Kyoko Hasegawa31110.66
Liang Li41511.12
Hiroshi Yamagushi500.34
Satoshi Tanaka66120.61