Automatic Generation of High-Quality Building Models from Lidar Data

Authors:
Franz Rottensteiner
Affiliations:
-
Venue:
IEEE Computer Graphics and Applications
Year:
2003

Citing 1
Cited 9

An Experimental Comparison of Range Image Segmentation Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence

Scanning Scene Tunnel for City Traversing

IEEE Transactions on Visualization and Computer Graphics
Per-field urban land use classification based on tax parcel boundaries

International Journal of Remote Sensing
Fast and extensible building modeling from airborne LiDAR data

Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
3D terrestrial LIDAR classifications with super-voxels and multi-scale Conditional Random Fields

Computer-Aided Design
Residential Building Reconstruction Based on the Data Fusion of Sparse LiDAR Data and Satellite Imagery

ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
A Variational Approach to Semiautomatic Generation of Digital Terrain Models

ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
3D building reconstruction from LiDAR data

SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery

PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Survey and practice of 3d city modeling

Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment

Quantified Score

Hi-index	0.00

Visualization

Abstract

This article presents a method for the automated generation of 3D building models from directly observed point clouds generated by Lidar. Building regions are detected automatically, and then a curvature-based segmentation technique detects roofs. These roof planes are grouped to create polyhedral building models. In this grouping process, the shapes of the roof plane boundaries are determined, and the whole model is improved by an overall adjustment using all available sensor information and, if possible, geometric constraints. The article describes the existing modules and those still in the implementation phase, and discusses the issue of integrating aerial images into the reconstruction process to increase the geometric quality of the reconstructed models.