nagnitude 
ined as a 
One can 
intensity 
irameters 
ling to a 
d motion 
frame is 
otational 
lustrated 
indicate 
. and T, 
em. [he 
e motion 
fusion of 
1995 
  
335 
Table 3: Estimated motion parameters with range information only. 
  
Parameters | 1 > 2 | 2>3 |3=—4 | 4=5 | 5=6 
-0.11 | -0.12 0.93 0.84 0.36 
3.39 3.69 273 7.35 10.25 
2.16 1.26 11.69 20.52 18.45 
-0.21 0.45 0.57 10.62 9.79 
-0.12 -0.3 -0.23 -0.39 -0.51 
-0.18 0.09 0.38 0.87 0.21 
10 10 36 30 26 
  
  
  
  
  
  
  
  
  
  
2 REPENS 
  
6. CONCLUSION 
This paper described a method capable of estimating 3-D motion parameters from a sequence of range and intensity 
images without having to solve the traditional correspondence problem between successive images. Furthermore, it 
was demonstrated that by using a sequence of intensity images in addition to range images, one can impove the 
speed and the accuracy of motion parameter estimation. This method has at least two advantage: range images 
enable one to interpret more complicated motions since they represent the real 3-D shape; and, even though multiple 
features can be seen in one image, that does not always mean that one can see them in another due to occlusion. 
The present method does not suffer from this particular limitation, since it is not based on an image feature matching 
procedure. 
ACKNOWLEDGEMENTS 
The authors would like to thank Luc Cournoyer for the range image acquisitions. This work also benefited from 
discussions with Guy Godin, Marc Rioux, and Francois Blais. 
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IAPRS, Vol. 30, Part 5W1, ISPRS Intercommission Workshop “From Pixels to Sequences”, Zurich, March 22-24 1995