Full text: Proceedings, XXth congress (Part 2)

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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV. Part B2. Istanbul 2004 
3.3.2 Second step - reading camera calibration and 
measuring fiducials — to determine IO. Camera calibration 
parameters are stored in the database and by connecting the 
image to its corresponding camera calibration, the user must 
measure pixel coordinates for all fiducials found in the image 
(fig.1, red crosses). To facilitate the manual measurement, 
Mapcheck pans and zooms in, close to the image location of 
the fiducials — one by one. Then the operator only has to 
point out its exact image pixel location. 
3.3.3 Third step — verification of image rectification and 
archiving metadata. It is possible to verify the precision of 
the VT parameters (IO and rotation) calculated for an image, 
by draping the database vector data as was used for image 
rectification. This makes it possible to judge, if points are 
measured correctly. When ground control points and fiducials 
are accepted, metadata is put in the database. 
3.4 VT Control procedure examples 
To illustrate different aspects of the implemented VT 
methodology, examples are presented and discussed next: 
3.4.1 Image-overview and -loading. With model vector 
data loaded as a map in Mapcheck, it is possible to get a 
visualization of all images that are ready for VT module 
prepared, and cover all or part of the model (fig.2). 
From this, one can choose the best image offering best 
coverage of the current model. When "right clicking? with 
the mouse, it is possible to load that raw image, having its 
photo center closest to the mouse cursor position (fig.2). It is 
possible to toggle between all raw images that are ready for 
VT presentation in this way. Loading a raw image with 
vector data on top, only takes a few seconds. 
  
  
         
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Figure 2. Shown is a block of update-data to be controlled - 
together with the images, ready for photogrammetric 
transformation of vector data (X, Y, Z) in that area. Image- 
coverage are shown with red lines. These are shown 
photogrammetrically, from the photocenter of the active photo 
3.4.2 Single object error. Having vectordata active and 
loading a raw image in VT mode, the vector data are draped 
on the image as defined in the photogrammetrical metadata 
stored in the database (calculated IO and D, as in 3.3, from all 
ready verified TOP10DK objects). 
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As shown in fig.3, the VT module gives a very high 
correlation between vector data and the raw image, and most 
objects are matched exactly to their appearances. Vector data 
is at their positions even when they are not straight lines 
because the photogrammetric displacement is adapted. It can 
be seen that when a object is digitized with a wrong Z 
coordinate, then the vector-object will be shown displaced 
away from its correct image-position (fig.3, a small building 
at top). The height of that displaced building object is 
measured as 0 meters, where as the correct building height 
should be around 70 meters asl. 
3.4.3 Systematic object errors. When displacements are 
general in a model, the reasons could be failures in 
parameters for the photogrammetric transformation of vector 
data or it could be systematic error concerning the image- 
orientations (AT setup) used by contractors. VT-rectification 
parameter errors can be checked by using neighboring images 
covering the same area or alternatively using independent 
ground control points for the calculation. 
Systematic errors due to errors in the original image- 
orientation (AT) could be hard to recognize in this workflow, 
because data from the database, might include errors, is used 
for calculating the rectification parameters. If there is any 
doubt about the database data-quality, then control has to be 
done by use of independent ground control points. 
  
  
Figure 3. Example of Vector Transformation on raw image. The 
vector building shown close to silo has wrong Z value (0 m should 
be 72 m), and is displaced from its correct position by the road. 
  
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Figure 4. Same area as shown in fig. 3, from the polynomial 
rectified image (same fiducial and GCP°s). Big displacements. 
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