Full text: Proceedings; XXI International Congress for Photogrammetry and Remote Sensing (Part B1-3)

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
1075 
P2 
-0.005 
0.0647 
-0.0006 
-0.0034 
-0.0034 
Y 
0 
0 
0 
0.0046 
0 
Table.l the coefficient of the camera model and the calibration results 
experiment 1 
experiment 2 
experiment 3 
experiment 4 
experiment 5 
image: 
image: 
image: 
image: 
3D calibration 
fig-1, fig-2 
fig-1, fig-2, fig.3 
fig.3, fig.4 
fig.3, fig.4, fig.5 
result 
fx 
4093.1739 
4092.8528 
4093.4573 
4091.1457 
4092.9533 
fy 
4093.1739 
4092.8528 
4093. 4573 
4091.1457 
4092.9533 
Uo 
1613.6447 
1613.5213 
1599.6447 
1593.4342 
1612.9712 
Vo 
1203.3241 
1209.7321 
1201.3241 
1200.8646 
1210.3524 
ki 
-0.1196 
-0.0232 
-0.1196 
-0.1260 
-0.0231 
k 2 
0.0233 
0.0183 
-0.1196 
0.0901 
0.0045 
k 3 
0 
0 
0 
0 
0 
Pi 
-0.0011 
-0.0009 
-0.0011 
-0.0009 
0.0005 
P2 
-0.0012 
-0.0001 
-0.0012 
-0.0011 
0.0003 
Y 
0 
0 
0 
0 
0 
Table.2 Photography model and the calibration results 
The shape of the control points effect the results actually. 
Because the centre of the shape is not the circle centre any more. 
The photography model influent the results, too. In table 2, we 
use the images in different photography ways. 
When the model doesn’t cover the whole image, the result is 
bad. When the model image is not in the centre of the image 
(fig.5), the result is wrong! 
At last, when the size of the object model is similar to the size 
of the measurement object, the measurement precision is the 
highest. You can see, fixed focal length, camera within a certain 
distance of imaging is clear, because the cameras have a certain 
depth of field. 
Fig. 9 the modelling object 
4. CONCLUSION 
By experiments, we analyse the influence factors in the 
calibration: the camera and lens, the shape of control points, 
photography model and the scale between calibration object and 
measurement. Appropriate model can get the right result 
quickly, and the position of the model in the image effects the 
calibration result directly. The control points should cover the 
whole image evenly. The cross control point is better than circle 
points. The more similar the size of object model and the 
measurement object, the higher precision the calibration has. 
Actually, each of them plays an important part in calibration. 
We can get higher precision result based on considering those 
influence factors. And the experiments in the end show that the 
work is worthy. It means that we should take those factors into 
account. 
REFERENCES 
Janne heikkila. Geometric Camera Calibration Using Circular 
Control Points. IEEE Transactions on pattern analysis and 
machine intelligence. Vol.22. No. 10. October 2000. 
Triggs B. 1998. Auto-calibration from planar scenes. [A], In: 
Proceedings of 5th European Conference on Computer Vision 
[ C ], Freiburg Germany: 89-105. 
Tsai RY. 1987, A versatile camera calibration technique for 
high-accuracy 3-D machine metrology using off-the-shelf TV 
cameras and lens. IEEE Journal on Robotics and Automation, 
RA-3(4): 323-344. [J] 
Yongjun Zhang, 2002. Camera Calibration Using 2D DLT and 
Bundle Adjustment with Planar Scenes, Geomatics and 
Information Science of Wuhan University, Vol.27 No.6. 
Zhengyou Zhang, A Flexible New Technique for Camera 
calibration. December 2, 1998.
	        
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