tor has to estimate the location of hidden corners from the conThis paper presents a novel method for semi-automatically jugate images. This procedure is tedious and inefficient and constructing building models from photogrammetric 3D line has a limited accuracy, especially for connected buildings in segments of buildings, i.e., their roof edges. The method, which densely built-up areas. we call “Split-Merge-Shape” (SMS), can treat both complete Weidner (1997), Haala and Brenner (1998), and Brenner line segments as well as incomplete line segments due to image (2000) proposed the use of digital surface models (DSMS )t o reocclusions. The proposed method is comprised of five major construct 3D building models. The DSM data can be generated parts: (1) the creation of the Region of Interest (ROI) and pre- automatically using stereo-pairs, or can be obtained from airprocessing, (2) splitting the model by using the 3D line seg- borne laser scanning (Lohr, 1996). The problem is that precise ments to construct a combination of roof primitives, (3) merging buildingboundaries cannotbewell defineddue tothesegmenconnected roof primitives to complete the boundary of each tation of DSMS. Therefore, other complementary data, such as building, (4) shaping each building rooftop by connected ground plans of the building outlines, are necessary to assure coplanar analysis and coplanar fitting, and (5) quality assur- the reconstruction. This limits the practicability of the ance. The experimental results indicate that the proposed approach. method can soundly rebuild the topology from the 3D line In order to increase efficiency, Fischer et al. (1998) and segments and reconstruct building models with up to a 98
[1]
Josef Jansa,et al.
THE GENERATION OF TRUE ORTHOPHOTOS USING A 3D BUILDING MODEL IN CONJUNCTION WITH A CONVENTIONAL DTM
,
1998
.
[2]
Claus Brenner,et al.
Interpretation of Urban Surface Models Using 2D Building Information
,
1998,
Comput. Vis. Image Underst..
[3]
Jan-Peter Muller,et al.
A technique for 3D building reconstruction
,
1998
.
[4]
Andrew Zisserman,et al.
A PLANE-SWEEP STRATEGY FOR THE 3D RECONSTRUCTION OF BUILDINGS FROM MULTIPLE IMAGES
,
2000
.
[5]
Olof Henricsson,et al.
The Role of Color Attributes and Similarity Grouping in 3-D Building Reconstruction
,
1998,
Comput. Vis. Image Underst..
[6]
Armin B. Cremers,et al.
Extracting Buildings from Aerial Images Using Hierarchical Aggregation in 2D and 3D
,
1998,
Comput. Vis. Image Underst..
[7]
Uwe Weidner.
Digital Surface Models for Building Extraction
,
1997
.
[8]
Claus Brenner.
TOWARDS FULLY AUTOMATIC GENERATION OF CITY MODELS
,
2000
.