Name
Abstract | ||
|---|---|---|
Methods for generating accurate building models from lidar data have received considerable attention in the recent literature. Many of the proposed techniques examine the data to define dominant planes in the structure, then intersect these planes to determine the location of internal edges and vertices. However, since most airborne lidar datasets are collected from near-nadir orientations, there are usually very few data points that lie on vertical surfaces. As such, it is usually difficult to determine the planes corresponding to exterior walls using data points on these walls. However, if we assume that exterior walls are oriented directly under the outer boundary of the roof structure, we may identify the geometry of these walls by modeling the 2D shape of the building exterior. This paper presents a robust approach for extracting this exterior boundary directly from the lidar data. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/IGARSS.2008.4778933 | IGARSS |
Keywords | Field | DocType |
modeling,buildings,shape,index terms— lidar,digital images,geometry,remote sensing,laser radar,lidar,solid modeling,robustness,probability density function,indexing terms,data mining | Data point,Computer vision,Vertex (geometry),Topographic map,Computer science,Remote sensing,Robustness (computer science),Lidar,Artificial intelligence,Roof,Probability density function,The Intersect | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephen R. Lach | 1 | 2 | 1.38 |
| John P. Kerekes | 2 | 194 | 35.38 |