Towards Globally Optimal Normal Orientations for Large Point Clouds

Various processing algorithms on point set surfaces rely on consistently oriented normals (e.g. Poisson surface reconstruction). While several approaches exist for the calculation of normal directions, in most cases, their orientation has to be determined in a subsequent step. This paper generalizes...

Full description

Saved in:
Bibliographic Details
Published in:Computer graphics forum Vol. 36; no. 1; pp. 197 - 208
Main Authors: Schertler, Nico, Savchynskyy, Bogdan, Gumhold, Stefan
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.01.2017
Subjects:
Algorithms
computational geometry
digital geometry processing
Energy conservation
Graphs
I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling‐Geometric algorithms, languages and systems
Mathematical analysis
modelling
Optimization
Orientation
Patches (structures)
Propagation
Reconstruction
Solvers
Tasks
Three dimensional models
ISSN:0167-7055, 1467-8659
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Various processing algorithms on point set surfaces rely on consistently oriented normals (e.g. Poisson surface reconstruction). While several approaches exist for the calculation of normal directions, in most cases, their orientation has to be determined in a subsequent step. This paper generalizes propagation‐based approaches by reformulating the task as a graph‐based energy minimization problem. By applying global solvers, we can achieve more consistent orientations than simple greedy optimizations. Furthermore, we present a streaming‐based framework for orienting large point clouds. This framework orients patches locally and generates a globally consistent patch orientation on a reduced neighbour graph, which achieves similar quality to orienting the full graph. Various processing algorithms on point set surfaces rely on consistently oriented normals (e.g. Poisson surface reconstruction).While several approaches exist for the calculation of normal directions, in most cases, their orientation has to be determined in a subsequent step. This paper generalizes propagation‐based approaches by reformulating the task as a graph‐based energy minimization problem and presents a streaming‐based out‐of‐core implementation.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12795