t BS. Istanbul 2004
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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004
used to define the datum, since only 6 exterior orientation
parameters are datum-dependent. The other parameters were
well determined by tie points. However, in the mentioned
networks, due to the specific geometry of the camera stations,
the camera constant was defined as a priori known parameter to
avoid high correlativity of this parameter with check point
coordinates. In addition, in the second network tumbling
parameters were defined as a priori known parameters since
they cannot be determined with a few control points. Although
tumbling parameters are not datum-dependent, these parameters
model the partial deviations of the orientation parameters of the
camera during rotation. Therefore, for a good and reliable
estimating, many control points, depending on the number of
the tumbling parameters are necessary. We estimated the
tumbling parameters of the EYESCAN in the camera calibration
process using all control points.
Table 2. Results of accuracy test (without tumbling modeling)
Number of check points 151
Number of control points 3
RMSE of check points (X, Y,Z) (mm) | 9.72, 3.72, 3.60
STD of check points (X, Y,Z) (mm) 1.68, 0.64, 0.60
Gy (pixel) 0.17 (1.36 microns)
Table 3. Results of accuracy test (with tumbling modeling)
Number of check points . 151
3
Number of control points 3
RMSE of check points (X,Y,Z) (mm) | 1.22, 1.04, 0.84
STD of check points (X,Y,Z) (mm) 1.58, 0.60, 0.54
ô, (pixel) 0.16 (1.28 microns)
5. CONCLUSIONS
We developed an advanced sensor model for panoramic
cameras and showed its accuracy performance. We indicated
the improvement of the sensor model by the modeling of the
tumbling for two terrestrial panoramic cameras EYESCAN and
SpheroCam. We measured the tumbling of the SpheroCam
using a physical instrument, an inclinometer. The tumbling of
the EYSCAN and also the SpheroCam was estimated after
bundle adjustment process, in which the tumbling parameters
were defined as additional parameters. We performed self-
calibration with/without tumbling parameters for EYESCAN
and SpheroCam to show the effect of the tumbling modeling.
The estimated standard deviations for the observations in image
space are 0.59 pixel for the SpheroCam and 0.33 pixel for the
EYESCAN in the case of using all mentioned additional
parameters, which shows subpixel accuracy for these dynamic
systems.
We also investigated the minimal number of control points for
determining additional parameters. For the accuracy test 3
control points and 151 checkpoints were used, in which
tumbling parameters were considered as a priori known
parameters. The achieved accuracy in object space is 1.22, 1.04,
0.84 mm for the three coordinate axes (X, Y, Z) and is
reasonable compared to the computed standard deviations. As
mentioned before, tumbling parameters were determined in a
camera calibration by means of control points. However, other
methods should be investigated for determining the tumbling
parameters, such as integration of a real time inclinometer or
using additional object space information like straight lines,
right angles, etc.
The accuracy test with minimal number of control points
confirmed that with these new devices we have additional
powerful sensors for image recording and efficient 3D
modeling. For the near future we plan to investigate further into
aspects of network design based on the characteristics of the
panoramic cameras and 3D object reconstruction.
ACKNOWLEDGEMENTS
We appreciate the cooperation of D. Schneider, TU Dresden,
who provided us with the image coordinates and control point
coordinates for the testing of the EYESCAN camera. We are
also grateful to Prof. Dr. L. Hovestadt, ETH Zurich, who rented
us his group's SpheroCam for the testfield investigations.
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