Full text: Proceedings, XXth congress (Part 3)

   
  
  
  
  
  
  
    
  
  
  
   
  
  
   
  
  
  
  
  
  
  
  
  
  
   
   
   
   
  
  
  
  
  
   
   
  
   
    
   
  
  
   
   
   
  
   
    
   
    
  
  
   
    
  
  
  
  
   
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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
  
  
  
  
  
Object total matches | matches used for | inliers | outliers 
epipolar geometry 
aerial image pair | 67 67 39 8 
aerial image pair 2 51 51 42 9 
turntable images 'Obi' 229 68 66 2 
virtual turntable images 282 84 80 4 
Valbonne image pair 112 50 41 9 
  
  
  
  
  
Table 1: Evaluation of the matching performance. Results are given for 5 image pairs. Note that for the turntable images 
as well as for the virtual turn table scene most of the inliers lie inside a planar region, for the aerial image pairs several 
matches lie on depth-discontinuities where the Zwickel-based descriptor is well suited. For the Valbonne image pair 
several matches were found at depth discontinuities since many prominent lines were found on the borders of planar 
regions. 
14 seconds on a Pentium 4 machine with 2.4 GHz. 
5 CONCLUSION 
We described a novel approach for computing affine invari- 
ant descriptors from Zwickels. Our experiments show, that 
these descriptors are invariant against viewpoint changes 
as well as illumination changes. Our method is suitable 
for images where a sufficient number of lines and therefore 
Zwickels can be extracted and the sectors inside the Zwick- 
els provide enough texture information to distinguish com- 
peting candidates. Further possible improvements are the 
use of more complex distance measures for histogram com- 
parison, such as the earth movers distance. In the next set 
of experiments we plan to test the method also in an object 
recognition context. 
ACKNOWLEDGMENTS 
This work has been done in the VRVis research center, 
Graz and Vienna/Austria (http://www.vrvis.at), which is 
partly funded by the Austrian government research pro- 
gram Kplus. Horst Bischof acknowledges the support of 
the Kplus competence center Advanced Computer Vision 
(ACV) funded by the Kplus program. The authors wish 
to thank Sandra Ober for providing the turntable data and 
Konrad Schindler for providing the virtual turntable se- 
quence. 
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