Paper Info
Title
Aerial 3D Building Detection and Modeling From Airborne LiDAR Point Clouds
Abstract
A fast, completely automated method to create 3D watertight building models from airborne LiDAR point clouds is presented. The proposed method analyzes the scene content and produces multi-layer rooftops with complex boundaries and vertical walls that connect rooftops to the ground. A graph cuts based method is used to segment vegetative areas from the rest of scene content. The ground terrain and building rooftop patches are then extracted utilizing our technique, the hierarchical Euclidean clustering. Our method adopts a “divide-and-conquer” strategy. Once potential points on rooftops are segmented from terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential building footprints. For each individual building region, significant features on the rooftop are further detected using a specifically designed region growing algorithm with smoothness constraint. Boundaries for all of these features are refined in order to produce strict description. After this refinement, mesh models could be generated using an existing robust dual contouring method.
Year
DOI
Venue
2013
10.1109/JSTARS.2013.2251457
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Keywords
DocType
Volume
airborne radar,optical radar,terrain mapping,vegetation mapping,3D watertight building models,aerial 3D building detection,airborne LiDAR point clouds,contouring method,divide-and-conquer strategy,ground terrain,hierarchical Euclidean clustering,individual building region,mesh models,multilayer rooftops,potential building footprints,rooftop features,rooftop patches,segment vegetative areas,smoothness constraint,terrain areas,vegetative areas,3D,LiDAR,building,graph cuts,modeling,region growing,vegetation
Journal
6
Issue
ISSN
Citations 
3
1939-1404
2
PageRank 
References 
Authors
0.38
0
2
Name
Order
Citations
PageRank
Sun ShaoHui125129.46
Carl Salvaggio254.83