Xo [m] Yo [m] Zo[m] w[rad] ¢[rad] K[rad] 
STEREO-PAIR #1 
left 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 
#std 0.00000 0.00000 0.00000 0.00000 0.00012 0.00005 
right 1.83000 0.00000 0.00000 0.10000 0.10000 0.10000 
#std 0.00000 0.00000 0.00000 0.00000 0.00012 0.00004 
STEREO-PAIR #2 
left 1.50000 0.00000 -23.99000 0.00000 0.00000 0.00000 
#std 0.00288 0.00073 0.00359 0.00002 0.00012 0.00008 
right 3.33000 0.00000 -23.99000 0.10000 0.10000 0.10000 
#std 0.00288 0.00087 0.00417 0.00003 0.00012 0.00008 
STEREO-PAIR #3 
left 2.99000 1.00000 -48.00000 0.00000 0.00000 0.00000 
#std 0.00557 0.00040 0.00460 0.00003 0.00012 0.00009 
right 4.82000 1.00000 -47.99000 0.10000 0.10000 0.10000 
#std 0.00557 0.00055 0.00467 0.00003 0.00012 0.00009 
STEREO-PAIR #4 
left 4.49000 2.00000 -70.00000 0.00000 0.00000 0.00000 
$std 0.00814 0.00054 0.00623 0.00003 0.00012 0.00009 
right 6.32000 2.00000 -70.00000 0.10000 0.10000 0.10000 
#std 0.00814 0.00063 0.00633 0.00003 0.00012 0.00009 
| 
STEREO-PAIR #5 | 
left 5.99000 1.00000 -90.00000 0.00000 0.00000 0.00000 
#std 0.01047 0.00093 0.00840 0.00003 0.00012 0.00009 
right 7.82000 1.00000 -90.00000 0.10000 0.10000 0.10000 
#std 0.01047 0.00100 0.00850 0.00003 0.00012 0.00009 
Table 2: Final Adjusted Orientation Parameters for Simulated 
Sequence ; 
Large, sparse design matrices such as those Lawson, C.L., and Hanson, R.J., 1974. Solving Least- 
Squares Problems. Prentice-Hall, Englewood Cliffs, 
   
  
  
  
  
   
  
  
   
    
  
   
  
   
   
  
  
  
  
  
  
  
  
  
  
  
  
   
  
  
  
  
  
  
   
   
  
   
   
  
    
frequently encountered in photogrammetry can be 
readily exploited by Givens Transformations. In the 
triangulation of a strip of several stereo-pairs with 
a large number of points, however, memory is always 
a concern. One possible solution to the problem 
would be to maintain a strip no longer than the 
number of stereo-pairs over which tie points have an 
influence. For example, if tie points from the first 
stereo-pair in a strip are no longer visible in the 
fourth stereo-pair, then the first could be dropped 
and the strip would now begin with the second. In 
this way no more than three stereo-pairs would be in 
memory at any time. 
The approach depicted in this paper can be utilized 
in vehicles other than the van described here. For 
example, positioning from boats, trains, and 
airplanes is possible. The method described for 
tying together a strip of stereo-pairs is not limited 
to mapping applications. Any problem involving 
sequential imaging can potentially be approached in 
this manner. Examples would include biomedical 
stereo imaging and autonomous vehicle navigation 
which is becoming a very popular topic of research 
due to the rapid development of intelligent vehicle 
highway systems (IVHS). 
REFERENCES 
Blais, J.A.R.,1983. Linear Least-Square Computations 
Using Givens Transformations. The Canadian Surveyor. 
Vol. 37, No. 4, pp. 225-233. 
Bossler, J., Goad, C., Johnson, P., Novak, K., 1991. 
GPS and GIS Map the Nations Highways. Geo Info 
Systems, March,1991, pp.27-37. 
Gentleman, W.M., 1973. Least-Squares Computations by 
Givens Transformations Without Square-Roots. Journal 
of the Institute of Mathematical Applications, 
No. 12, pp.329-336. 
Gruen, A., 1982. An Optimum Algorithm for On-Line 
Triangulation. Proceedings of the Symposium of 
Commission III of the ISPRS, Helsinki. 
Gruen, A., 1985. Algorithmic Aspects in On-Line 
Triangulation. Photogrammetric Engineering and Remote 
Sensing, Vol. 51, No. 4, pp. 419-436. 
New Jersey. 
Mikhail, E.M., and Helmering, R.J., 1973. Recursive 
Methods in Photogrammetric Data Reduction. 
Photogrammetric Engineering, Vol. 39, No. 9, pp. 983- 
989. 
Novak, K., 1990. Integration of a Stereo-Vision 
System and a GPS-Receiver in a Vehicle. Presented 
Paper, Vision '90 Conference. 
Novak, K., Johnson, P., and Orvets, G., 1991. Stereo 
Imaging Meets GPS for a Highway Database. Advanced 
Imaging, April, 1991, pp. 38-41.