Full text: Proceedings, XXth congress (Part 3)

    
    
     
    
    
  
    
     
   
   
    
    
    
   
    
   
    
     
   
      
     
    
     
     
    
    
  
  
  
   
   
    
  
        
   
    
      
   
    
    
   
    
   
   
33. Istanbul 2004 
12 to 15 meters, 
> laser strips. The 
1gs or part of the 
buildings were 
lative orientation 
. pulse was used 
seen in Figure 2. 
le roofs and flat 
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ntation of many 
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of Figure 3. The 
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1 color-coding. 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
Typically, the color-coding is done according the distance from 
the camera location or according the altitude. 
The interactive method requires enough visible features on the 
image footprint. These features can be buildings, road signs, 
fences and even trees, for example. Specially, if the close-range 
images are used, the image footprint is usually quite limited and 
may contain too few distinguishable targets for accurate 
orientations. The panoramic images provide ultra-wide viewing 
angle and therefore better ensures finding reliable set of features 
within the image. Figure 3 is a part from panoramic image 
mosaic, created from concentric image sequences. This method 
of mosaicing is described in Haggrén et al. (1999) and Póntinen 
(2000). 
The interactive orientation method is applicable also for direct 
relative orientation of two laser point clouds. Firstly, the first 
point cloud is superimposed to the plain image plane, leading 
the situation that actually equals to a normal central perspective 
image. Secondly, the interactive orientation method is applied 
to find relative orientation between this image of the first point 
cloud and the other laser data set. 
With synthetic images, there are no limitations for the 
perspective of inspecting. Therefore, angle of view can be 
chosen in a way the tie features are most visible. Typically, the 
reference area should be investigated, at least, at two 
perpendicular directions to ensure good accuracy in each 
direction. In this research, the test sites were inspected from two 
to six different angles of view. The described method to adjust 
two laser point clouds directly into the common coordinate 
system was applied the first time in Hyyppä et al. (2003) in the 
forestry areas. 
  
Figure 3. Laser scanning data provide good coverage of the 
building. However, some small deformations are 
detectable. This image covers about 23 % of the 
original panoramic image and laser point cloud. 
Comparison between laser strips was done in all thirty-nine 
small test sites (Figure 2). The laser strip 2 was selected as a 
reference strip and the other strips were oriented to that. 
Because the test sites were quite small ones, only the shifts 
between point clouds were solved. If there was any detectable 
shift (e.g. in Figure 4), the difference was measured. Each 
orientation was done independently, without knowing the 
differences in surrounding test sites. 
  
A) : TR a B) 
A 
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Figure 4. The planimetric shift of the building between laser 
strips 2 (black) and 5 (white) is visible from two 
different central perspectives. A) The shape of the 
roof. B) The wall and the edge of the roof. 
4. RESULTS 
During the orientation process, it became obvious that the 
differences should be presented in the along-track, across-track 
and height direction. This is primarily, because the gaps in 
scanning geometry (Figure 1) caused problems in many test 
sites for orientations in across-track direction. In this research, 
the corrections were measured only, if some differences were 
detectable. Therefore, the distinct shift could be easily 
underestimated, if it was not possible to improve orientation 
due the scanner properties. To reduce this problem, some of the 
Worst test sites were discarded from the across-track direction. 
The results are presented in Tables I, 2 and 3. 
  
  
  
  
  
  
  
  
  
  
Strip 2-3 | Strip 2-4 | Strip 2-5 | Strip 2-6 
Mean [m] 0.050 -0.005 0.064 -0.010 
Std [m] 0.039 0.018 0.041 0.023 
Max [m] 0.150 0.025 0.136 0.045 
Min [m] -0.009 -0.041 -0.010 -0.078 
  
  
Table 1. Differences in flight direction (39 samples per strip) 
  
  
  
  
  
  
  
  
  
  
Strip 2-3 | Strip 2-4 | Strip 2-5 | Strip 2-6 
Mean [m] -0.012 0.003 -0.019 -0.005 
Std [m] 0.027 0.015 0.034 0.019 
Max [m] 0.018 0.037 0.025 0.035 
Min [m] -0.085 -0.020 -0.099 -0.039 
  
  
Table 2. Differences in across-track direction (20 samples per 
  
  
  
  
  
  
  
  
  
  
strip) 
Strip 2-3 | Strip 2-4 | Strip 2-5 | Strip 2-6 
Mean [m] 0.001 -0.003 -0.002 -0.014 
Std [m] 0.011 0.008 0.011 0.011 
Max [m] 0.027 0.014 0.025 0.002 
Min [m] -0.025 -0.027 -0.022 -0.043 
  
  
Table 3. Differences in elevations (39 samples per strip) 
The flight direction of the strips affects remarkably in the 
obtained planimetric errors both in along- and across-track 
directions. However, such phenomenon is not visible from the 
heights. If the differences between strips 3 and 5 are examined, 
the bias of only -0.014 m and standard deviation of 0.032 m in 
flight direction can be found. Correspondingly, the bias in 
across-track direction is 0.006 m with standard deviation of 
0.027 m. 
  
	        
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