ation estimate 
  
  
edicted | 
del 2 = ^ 
LZ. 
50 180 
© 
  
  
  
  
30 60 90 120 150 180 
Time, s 
Figure 7. Recovered orientation angle 9 
  
28 — —3 
  
  
2% C ! l sareassesestutass; model 
30 60 90 120 150 180 
Time, s 
Figure 8. Recovered orientation angle x 
  
The algorithm allows tracking objects given their 3D models. 
The convergence of the iterative algorithm depends on the 
availability of a good initial estimate. The procedure of 
recovering orientation parameters is ambiguous since there are 
many configurations that give rise to approximately the same 
projected contours. It may happen that the algorithm does not 
converge to the right optimum; this is due to the presence of 
false edges such as structures that are parallel to the true edges. 
Contours of the docking module should allow resolving the 
ambiguities in the determination of angles — however, since the 
docking module is small relative to the ISS a whole, the 
contribution of its contours in the whole misfit function is 
relatively modes. False edges often arise from shadows, 
especially long and contrasting shadows are cast by solar 
panels. In some flybys, additional distracting contours appear 
due to the texture of the Earth’s atmosphere. 
Then the algorithm was tested on a real video with only visual 
quality assessment. The real dataset contained telemetry 
information which was overprinted on the video sequence. 
Pixels belonging to textual information have been ignored by 
means of a binary mask which was created offline. Along with 
high noise level, flare and unfavorable lighting conditions it 
makes the problem of ISS image matching very difficult (Figure 
9). The total fraction of successful image matching for real 
video frames is 20-30% less then in case of modelling video. 
An example of successful fitting of the contour template to the 
real video frame is shown in Figures 10 and 11. 
CERTA EE 
EAE EDT ES] 
  
Figure 11. Contour obtained from found orientation 
4. CONCLUSION 
In this work we presented a method for estimating the 
orientation parameters based on the use of a highly detailed 
digital model of the ISS. One of specific features of the problem 
that we studied is that the ISS appearance on video frames 
substantially changes in the course of docking approach. 
Analysis shows that solving such a recognition and tracking 
problem requires different sets of algorithms depending on the 
range of distances between the SCS and ISS. 
In order to solve the exterior orientation problem for frame 
image of ISS the contour-based algorithms are used. Statistical 
tools such as Kalman filter are used to support the estimation 
process and real time object tracking. The substantial feature of 
the method presented in this work is the usage of a very detailed 
digital 3D model of ISS for subsequent generation of raster 
wireframe templates, used for detection in each frame and 
tracking of the ISS in video sequence. Algorithms based on the 
usage of wireframe templates show high robustness, but