ISPRS Commission III, Vol.34, Part 3A ,,Photogrammetric Computer Vision“, Graz, 2002 
  
is required in this approach as listed in Table (3). Results from 
manual SPR are also listed in the same table. One can see that 
the results from the traditional manual orientation and our 
approach (even in Experiment 4 where fewer object space roads 
were used and digitisation errors were introduced in the image 
space features) are comparable. In addition to the estimated 
parameters, we had obtained the correspondences between 
points in image and object space. 
Table 2: Experiments Summary. 
image space that had no correspondences in the object space in 
experiment 4 will be considered changes, as they belong to the 
same boundary of the object space entities that had been 
examined. In the next paragraph, we are examining changes that 
occurred locally between object and image space entities. 
Table 3. Estimated EOP and their initial (approximate) values 
together with the results from manual SPR. 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Object space data sets 
O1 (Fig. 4-a) O2 (Fig. 4-b) 
15 1572 5 799 
roads | points | roads | points 
[Image Il 15 Experiment 1 Experiment 2 
space | Fig. 4-c | roads 
data 55178 
sets points 
D 15 Experiment 3 Experiment 4 
Fig. 4-d | roads 
63397 
points 
  
  
  
  
  
  
  
  
  
  
  
Xo(m) Yo (m) Zo (m) 
Manual 600.00 -26.781 1014.894 
Appx. 450.0 100.0 900.0 
Exp. 1 599.762 -26.937 1014.842 
Exp. 2 599.797 -26.663 1014.699 
Exp. 3 599.722 -26.974 1014.818 
Exp. 4 599.245 -27.081 1014.754 
a Qo x 
Manual 0.584667 -0.867300 1.191474 
Appx. 9.0 -9.0 10.0 
Exp. 1 0.590318 -0.872063 1.185914 
Exp.2 0.572123 -0.871997 1.182790 
Exp. 3 0.589120 -0.870109 1.189792 
Exp. 4 0.594399 -0.895585 1.183058 
  
  
  
  
  
  
  
  
  
  
30 4» 80 mU 1X0 120 up Ju 
SST NTE Ew RU e 
(a) (b) 
150 150 
100 E à 100 i A t ; 
  
  
  
  
e m NE M 
agb A M 13 5 i 
| mme 4 77655 
| f | A Ï A A ) v \ | 
a | e ZA e [sf Ls] 
| Nam 121 Sa d 
100 m i4 [s] * ts] 100 \ 4 3] 
a ur 0 mw we Ba 100 — 50 a 50 100150 
(c) (d) 
Figure 3: Object space linear features O1 (a), and O2 (b), and 
image space linear feature without digitisation errors 
Il (c) and with digitisation errors I2 (d). Roads are 
labelled for further references. 
The correspondence between the image and the object space 
linear features as well as the consistency check described in 
section 3.2 have been performed. All the roads were reliably 
matched (see Figure 3). In this figure, corresponding road 
segments were given the same label. One should notice that we 
had realised the correct correspondences between higher level 
entities (road segments). Even when there is no one to one 
correspondence between higher-level image and object space 
entities (as in experiment 4, where 10 out of 15 road segments 
in the image space are not present in the object space), 
correspondences are reliably obtained. Moreover, the quality of 
the estimated parameters did not deteriorate. The 10 roads in the 
Non-matched points in the object space, after being projected 
into the image space, were significantly far from any of the 
points in the image space. Therefore all of them were 
considered as discrepancies. Among these non-matched points 
consecutive points were segmented and the longitudinal and the 
lateral distances from the corresponding road line were 
computed. Results from experiment 4 are listed in Table 4. We 
can see that the changes had been reliably detected. 
Table 4. Changes (discrepancies) between image and object 
space linear features, experiment 4. 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Discrepancies (Changes) in the object space 
o — 
T = Location 3 8 : 3 8 
2 m 5 2 = OQ Z © 
2E| BE xm | Ym [zm | £2 £2 
© > "uu EÀ 
zZ SS | 33 
2 3 -70.81 309.98 | 34.18 | 1.69 16.02 
2 17 56.71 200.27 | 3723 | 5649 | 211.53 
2 19 403.81 | 263.37 | 43.59 | 5746 | 141.1 
2 25 855.49 248 S3.03 5 67.6 | 20122 
2 19 1227.19 | 222.05 | 60.53 | 40.61 | 148.97 
3 13 1238.2 | -9128 | 67.05 | 44.96 | 114.61 
3 A 910 -104.28 | 61.59 | 28.59 | 30.53 
3 7 327.42 | -64.31 | 55.89 | 30.97 | 7242 
3 13 199.75 32.54 | 4781 | 4162 | 81.31 
3 12 -16.3 74.74 | 42.04 | 65.7 | 149.53 
5 13 1167.07 | -39973 | 76.26 | 23.1 49.28 
s 4 1169.49 | -444.77 | 76.8 1.04 13.29 
5 8 1199.87 | -564.32 | 8422 | 10.8 12.52 
3 10 1259 -592.19 | 94.94 | 6.84 16.94 
8 17 302.33 87.72 | 46.44 | 27.6 60.32 
8 31 274.23 | -141.86 | 51.63 | 56.78 | 105.73 
8 27 240.81 | -451.65 | 58.09 | 31.65 | 115.76 
15 8 590.49 | 351.71 | 46.08 | 14.74 | 28.01 
  
  
  
Examples of changes, which were detected, are shown in Figure 
4. It has to be noted that all the changes were reliably detected 
and their existence does not contribute to the estimated 
parameters. Therefore, we realised a robust estimator for the 
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