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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004 
  
  
  
Parameter 6, [Pixel] 
Exterior orientation 25.20 
Interior orientation 5.88 
Eccentricity of projection centre 5.63 
Non-parallelism of CCD line (2 components) 1.15 
Lens distortion 0.60 
Affinity 0.45 
Non-uniform rotation (periodical deviations) 0.24 
  
  
  
  
Tab. 2: 6, of spatial resection 
Translating the resulting 0 of 0.24 pixel into object space, we 
receive a lateral point precision between 0.1 (at 2 m distance) 
and 0.5 mm (at 10 m distance) when using a 35 mm lens. 
According to the length of the CCD line of 10,200 pixel, this 
value corresponds with a relative precision 1 : 42,000. 
In (Amiri Parian & Griin, 2003) further parameters in addition 
to physically defined parameters are used for the compensation 
of local systematics. For this purpose the panorama is divided 
into pieces, in which a polynomial approach is then used for the 
compensation of local remaining systematics. Thus Go = 0.23 
pixels was reached, which corresponds to the order of 
magnitude shown here. 
4, IMPLEMENTATION OF THE MODEL 
The mathematical model was implemented into different 
photogrammetric applications, with primary focus on a bundle 
block adjustment for panoramic images. 
4.1 Panoramic bundle adjustment 
Using the bundle adjustment, it is possible to determine object 
points, orientations and camera parameters simultaneously from 
two or more panoramas. An important goal during the 
development of the panoramic image bundle block adjustment 
was user friendliness, which means among other things that the 
computation should get along with as few as possible 
approximate values. The implemented solution requires only 
three object points to procure approximate values for the 
orientation of the panoramas and successively for all object 
points. These three object points can be realized for example by 
a small reference triangle placed into the object. The adjustment 
can be accomplished alternatively with a minimum datum 
solution, a certain number of control points or as free network 
adjustment. In Tab. 3 the results of two computations, an 
adjustment with minimum datum and a free network 
adjustment, both with 364 object points and 5 camera positions, 
are summarised. As expected, the standard deviations of the 
object coordinates are better in the free network adjustment. 
This effect can be explained by the datum point distribution. 
  
  
  
  
  
  
  
  
Fig. 10: Object points of calibration room of AICON 3D 
Systems GmbH incl. camera positions 
  
  
  
  
  
Minimum datum Free network 
adjustment 
Go [pixel] 0.22 
9x [mm] 0.48 0.33 
oy [mm] 0.45 0.27 
Oz [mm] 1.01 0.15 
  
  
Tab. 3: Results of panoramic bundle block adjustment of points 
in the calibration room 
Remaining systematic errors of the camera might result in 
object point coordinate errors and not show up in the results of 
the bundle adjustment. Therefore the computed object 
coordinates were compared with the reference coordinates of 
the calibration room. For the stabilization of the block geometry 
four well-distributed control points were used. From Tab. 4 it 
becomes obvious that the average value of the deviations 
amounts to ca. 0.5 mm for all three coordinate directions. It is 
not sure, however, whether the small discrepancy between 
bundle results and checkpoint deviations can be interpreted as a 
limitation of the accuracy potential of the camera, or whether 
the deviations are caused by the limited precision of the 
reference coordinates.