Full text: XVIIIth Congress (Part B3)

  
Figure 4: Basic concept of free-form curves in bundle 
block adjustment 
Note that the shape of S is completely described by a 
set of node points K. Parameter t describes the position 
of the foot (S(K,t) ) of point P on S. 
So, the unknowns of our least squares adjustment 
problem are the co-ordinates of the node points (K), the 
positions of the points along the curve (1) and the object 
co-ordinates of the curve points (P), and the orientation 
parameters (the rotational parameters and the 
projection centres) of the images. If the photographs 
have been taken with a calibrated camera, the 
elements of the inner orientation are well known. 
Considering parameters t unknown in the adjustment 
process enables optimisation of the positions of the 
nodes both laterally and along the curve (Forkert, 1993, 
pp. 221-228). If the distance between to consecutive 
nodes falls below a user specified threshold, one of the 
nodes will be deactivated automatically. 
The problem of “relative orientation“ can be solved if 
object curves exist which are visible in three or more 
images. For the following considerations let's 
concentrate on one object curve, only. If the images 
are not oriented, the bundles of rays running through 
the image curves do not intersect uniquely. So, the 
bundles have to be shifted and rotated until they 
intersect correctly in one spatial curve. At the same 
time, the shape of this tie curve will be determined. 
Consequently, the relative orientation of three or more 
images can be found by using an arrangement of tie 
curves. Note, that in general it is not possible to find 
homologous points in different images of the curve. So, 
our method is based on homologous curves instead of 
on homologous points. 
Questions for the minimum configuration of tie curves 
can be answered by replacing the curves by their 
significant tangents. A U-formed curve, for instance, 
consists of two significant tangents. Every tangent is 
described by four parameters in object space and by 
two parameters in image space, respectively. So, for 
example, the eleven parameters describing the relative 
orientation of three images can theoretically be 
determined by at least three U-formed curves. 
198 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B3. Vienna 1996 
4 IMAGE ORIENTATION 
4.1 Determination of approximate values 
In this test project, the local reference co-ordinate 
system was chosen arbitrarily by fixing seven 
orientational elements. The scale of this local co- 
ordinate system was estimated corresponding to the 
real object dimensions in order to get realistic r.m.s. 
errors in object space. 
An appropriate configuration of provisional tie curves, 
extracted from the images as described above, allows 
to determine initial values for the image orientation. The 
real image orientation will be carried out later on (see 
section 4.2), using tie curves cutted out from the 
provisional curves. 
In order to get provisional values for the image 
orientation parameters, the first step of calculation is 
carried out conventionally with points: the end points of 
the image curves are used as tie points. End points of 
curves imaged only partially might cause significantly 
large residuals and have to be eliminated by robust 
estimation. The results of the adjustment can be seen 
in table 1. 
  
  
No. images No. tie points r.m.s. error in 
image 
12 84 5mm 
  
  
  
  
  
Table 1 
Thereafter, the initial node positions of a provisional tie 
curve can be obtained through an approximation 
algorithm: Approximate curve points in object space are 
found by intersecting their image rays with the cone 
surface formed by the rays of another image. 
Afterwards, the algorithm distributes the nodes in 
regular intervals along the polygon of curve points. In 
this test project, the initial number of nodes was chosen 
automatically dependent on the number of curve points 
(one node per fifty curve points). In order to improve 
the initial node arrangement, the approximation process 
is completed by a curve adjustment with the 
approximated object points assumed to be constant. 
For the time being image orientation is quite inaccurate. 
Nevertheless 29 out of 40 provisional tie curves could 
be approximated as shown in figure 5. 
Experience shows, that it is advisable to refine the tie 
curve's shape before starting image orientation. The 
unknowns of this "curve reconstruction" task are: the 
co-ordinates of the node points, the positions of the 
points along the curve and the object co-ordinates of 
the curve points. The actual values of the orientational 
parameters are assumed to be constant. The 
automated iterative process of curve reconstruction 
consists of two main steps alternately applied: 
1) adjustment with a given number of nodes 
   
    
  
    
   
  
  
  
   
   
  
  
  
  
  
  
  
  
  
  
     
     
   
    
   
    
   
   
    
   
   
   
   
   
    
   
   
    
    
  
  
    
    
     
   
   
    
    
   
  
  
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