Full text: Proceedings, XXth congress (Part 3)

   
   
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Figure 8. Four screen shots in selected areas in the site of the 
24,887 buildings created for the city of Aalborg. 
5. CONCLUSIONS 
The overall performance of the algorithms is surprisingly good, 
considering the relatively low resolution of the laser scanning in 
combination with distortions caused by a very unfortunate 
interpolation of the raw data. In addition, the mutual 
displacements of the two datasets (footprints and laser 
scanning) are sometimes difficult to correlate, and undoubtedly 
the cause of many problems. In our case, creating a building has 
a success rate of 84 percent, although the qualities of these are 
not always satisfactory. 
In particular, the following algorithms are believed to be very 
efficient and general for the purpose: 
e Projected cluster area filter used for extraction of 
planes from Hough space. 
e Degenerate mesh filter where error detection is based 
on mesh welding techniques. 
These algorithms are innovative and not described in similar 
articles like e.g. [Vosselman, 2001]. 
However, there are a number of obvious problems and 
drawbacks of the methods described in this article. 
5.1 Height jump lines 
Currently, we have no method for detecting height jump lines, 
as the sampling resolution is considered too low for this 
purpose. Instead, by splitting the footprints into smaller units, 
the influence of height jump lines is reduced, as the footprints 
are often cut exactly at lines convergent to these. However, as 
the resolution of laser scannings increase, solutions of height 
jump lines are needed. 
5.2 Aligning ridges and gables 
In our methods we rely on using the Hough Transform for 
detection of planes in 9. Planes are among the most simple 
primitives in N°, but not necessarily the “atomic” unconstrained 
primitives of building roofs. 
In the case of roofs, some of the d.o.f. of a plane are often 
constrained by another adjacent plane on the other side of the 
ridge, just like the dependencies between the two sides of equal 
length in an isosceles triangle. A Ridge Plane Pair is two planes 
intersecting at the line of the ridge. Roof planes which have an 
angle of more than 20 deg from horizontal often have such 
accompanying planes. The line of intersection (the ridge) is in 
e 
    
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
most cases a strictly horizontal line, and the angle from 
horizontal is often the same for both planes. 
Figure 9. The  Isosceles Triangle is 
; : b 
constrained in the same manner 
as the Ridge Plane Pair. / f^, 
a 
Furthermore, planes are often strictly parallel to a line of the 
footprint, meaning that the orientation of a roof plane is 
achievable by rotating it from horizontal around an axis 
convergent to one of the footprint lines. 
Utilizing this knowledge on the dependencies of planes, major 
achievements in precision is expectable. The Hough Transform 
is a general method for detecting primitives in parameter space. 
The more complex primitives, the more parameters to describe 
these in parameter space, and thereby, more dimensions to 
sample and traverse. However, being able to set up constraining 
rules drastically reduces the number of samplings necessary in 
each dimension of parameter space. Consequently, it is possible 
to use the Hough Transform for detecting more complex 
primitives, which should be done in future research. 
6. ACKNOWLEDGEMENTS 
The laser scanning and ortho photos were provided by COWI 
A/S, Consultancy within Engineering, Environment and 
Economics. Geometries of footprints and cadastres from the 
technical feature map were provided by the Municipality of 
Aalborg. The authors thank both providers for making these 
data available. 
7. APPENDIX — PRE PROCESSING OF SOURCE DATA 
Proper pre processing of the source data is of vital importance 
for the reconstruction algorithms. 
7.1 Fixing geometries of footprints 
It is desirable that the footprints as much as possible reflect the 
actual 2D borders of the individual buildings. 
  
  
  
  
  
  
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Figure 10. The background upper picture shows a snapshot of 
raw footprints from the technical map. The lower 
front picture shows the resulting shapes of these 
footprints when cut by polygons of cadastres. 
   
    
    
   
    
   
  
    
  
  
  
  
   
   
    
   
     
    
    
  
  
  
  
  
  
  
  
   
    
    
    
     
  
   
  
   
   
   
   
    
   
  
  
  
   
   
   
   
   
    
   
    
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