TY - JOUR
T1 - Adaptive feature-conserving compression for large scale point clouds
AU - Eickeler, Felix
AU - Borrmann, André
N1 - Publisher Copyright:
© 2019 CEUR-WS. All rights reserved.
PY - 2019
Y1 - 2019
N2 - In this work we introduce a practical method for reducing big point clouds of buildings and infrastructure. The proposed method introduces bilateral filtering with a tailored set of evaluation functions, that will conserve as much information as possible. To determin the actual statistical parameters to perform this filtering and reason about our development, we investigate different point properties on a comprehensive dataset. The dataset contains artificial, photogrammetric and laser scanned point clouds and was made publicly available. We showcase our filtering method by preserving more information than voxel grid or density filters challenging even sparser photogrammetric datasets. Finally, we discuss some encoding strategies as well as the sweet spot between size and resolution.
AB - In this work we introduce a practical method for reducing big point clouds of buildings and infrastructure. The proposed method introduces bilateral filtering with a tailored set of evaluation functions, that will conserve as much information as possible. To determin the actual statistical parameters to perform this filtering and reason about our development, we investigate different point properties on a comprehensive dataset. The dataset contains artificial, photogrammetric and laser scanned point clouds and was made publicly available. We showcase our filtering method by preserving more information than voxel grid or density filters challenging even sparser photogrammetric datasets. Finally, we discuss some encoding strategies as well as the sweet spot between size and resolution.
UR - http://www.scopus.com/inward/record.url?scp=85069186053&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85069186053
SN - 1613-0073
VL - 2394
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 26th International Workshop on Intelligent Computing in Engineering, EG-ICE 2019
Y2 - 30 June 2019 through 3 July 2019
ER -