International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004
4. EXPERIMENTS
In order to test our approach we contacted a series of
experiments. In this setup we only used just a plane object in
our image. We created a simulated dataset for 16 different
sensor positions. For each position we have the coordinates in
real space and the supposed rotation angles. In figure 11 we can
see a top view of the setup and how an image is viewed in
station 7, while in table | we can see the orientation values for
each station in the local coordinate system. In this setup we
only processed the bold facade of the building.
1
Led
Station 1*7
Station2 *^
Station 3 =~
Station 4 =
Station 5 x
Station 6 «^
Ci
Station 7
Stations ” ,
Station 9 "
Station 10 F ;
Station 11 of l
Station 12 i à |
Station 13 Station 16
Station 14 en
Station 15
Figure 11 Simulation dataset setup.
Yo Q © K
Xo (m) Zo (m) (m) deg deg deg
Station 1 -83.8507 -29.5928 4 -75 5 30
Station 2 -81.2074 -37.9129 5 -70 10 25
Station 3 -77.8689 -45.9727 6 -65 15 20
Station 4 -73.8407 -53.7109 7 -60 20 15
Station 5 -69.1533 -61.0685 S. 285 25 10
Station 6 -63.8426 -67.9896 6 -50 20 5
Station 7 -57.9488 -74.4216 5 -45 15 0
Station 8 -51.5169 -80.3153 4 -40 10 -5
Station 9 -44.5958 -85.6261 34. 133 5 -10
Station 10 -37.2381 -90.3134 2.730 0 -IS
Station 11 -29.5 -94.3417 |] 23 -5 -20
Station 12 -21.4402 -97.6801 0 20 —10 — 25
Station 13 -13.12 -100.3035 o 18-45 30
Station 14 -4.603 -102.1916 -2 -10 -20 15
Station 15 4.013 -103.3303 -1 -5 -25 45
Station 16 12.7619 -103.7109 0 0 0 0
Table 1 Station Orientation Information
In Table 2 we can se he results for the recovery of the rotation
angles using the vanishing points approach. we can see that the
angles o, x were recovered very accurate while for the rotation
¢ the highest error in the recovered accuracy was around 2
degrees, which is accurate enough for our applications. We also
run the full algorithm in a different dataset created using the
same stations but only ¢, and x rotation angles. The results are
presented in Table 3. We can see that for a total traveled
distance of 130 meters the errors are in the neighborhood of
centimeters.
Errors
q deg w deg K deg
Station | -0.054689 0.000071 -0.000001
Station 2 -0.283546 -0.000084 -0.000002
Station 3 -0.769276 -0.000021 0.000000
Station 4 -1.566688 0.000032 0.000005
Station 5 -2.689448 -0.000085 0.000001
Station 6 -1.763289 -0.000073 0.000003
Station 7 -0.992982 -0.000091 -0.000002
Station 8 -0.431297 0.000083 -0.000001
Station 9 -0.102587 -0.000026 -0.000003
Station 10 -0.000005 -0.000054 0.000000
Station 11 -0.083557 -0.000070 -0.000002
Station 12 -0.280196 -0.000008 0.000001
Station 13 -0.489229 -0.000007 -0.000002
Station 14 -0.591965 -0.000010 0.000002
Station 15 -0.466409 -0.000102 -0.000002
Station 16 0.000000 0.000000 0.000000
Std 0.731904 0.000055 0.000002
Table 2 Accuracy in rotation recovery
Errors X m Errors Z m Errors Y m
Station15 0.049373 0.000000 -0.000012
Station 14 0.095555 0.000000 -0.000401
Station 13 0.740550 -1.163700 0.067356
Station12 0.080210 -0.000100 -0.014127
Station! 1 0.106520 -0.000100 -0.016784
Station10 0.123070 -0.000100 -0.021921
Station9 0.129600 -0.000200 -0.027239
Station8 0.126160 -0.000200 -0.029113
Station7 0.113720 -0.000300 -0.030154
Station6 0.093610 -0.000300 -0.030232
Station5 0.067760 -0.000400 -0.029265
Station4 0.038540 -0.000500 -0.027232
Station3 0.008150 -0.000500 -0.024185
Station2 -0.020780 -0.000600 -0.030226
Stationl -0.046070 -0.000700 -0.036643
Std 0.175498 0.290207 0.024736
Table 3 Accuracy in Position recovery
5. FUTURE WORK
In this paper we presented a method for the recovery of
orientation between two consecutive frames using a method that
first determines the rotation angles and proceeds to determine
the translation between the two frames. Using the presented
approach we achieved very good results for the recovery of the
rotation angles but we used very accurate measurements in the
image points. We also achieved very good results in position
recovery, but we took into account only two of the three
rotation angles in the creation of our dataset. Another aspect of
the created dataset is that we only used one object (building
facade) in our approach. We are planning to further examine the
behavior of algorithm by creating datasets with different cases
of pathways. We will also like to examine how the algorithm
works with the addition of noise in image measurements, so we
will introduce noisy images and different kind of lens distortion
in our model, and the interior orientation parameters. Finally we
would like to explore the behavior of the algorithm when
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