Images were grabbed with 25 frames/second on miniDV 
media. 
From video frames it is possible to acquire semantic and metric 
data. To assure quality of metric data video camera must be 
calibrated. Camera calibration was carried out in two steps. In 
the first step only original camera lens were calibrated. In the 
second step there was mounted wide converter in front of 
original camera lens. For calibration field it was used the 
frontage of nearby hall with lot of precise constructed mesh of 
plate holders. There were taken 10 video snapshots of 
calibration filed from 10 different observing points. Image 
measurements for each plate holder on ten images were then 
introduced into computation of camera autocalibration 
procedure in the software package BING-F. Results of camera 
calibration are focus and distortion of the lens and principal 
point of the camera. To avoid problems with uncertainty of a 
pixel size it was used 1 pixel as an unit in all computations. 
  
  
  
  
  
  
  
  
  
Step Focus Principal Distortion 
point (max. value) 
Caml 850.98 (£0.78) 3.89, 6.21 5.53 
Cam 2 851.17 (£0.70) 3.49, 0.52 5.05 
Caml (we) | 573.05 (+0.41) | 0.63, 3.60 16.99 
Cam2 (we) 571.48 (+ 0.44) 0.81, 0.88 16.61 
  
  
  
Table 1. Results of camera autocalibration; all values are given 
in pixels 
With known parameters of video camera it is possible to 
resample images for distortion and perspective. 
  
  
Figure 2. Calibration for image perspective and distortion 
2.2 Data georeferencing 
The main tool for data georeferencing was GPS system. During 
the survey it is impossible to ensure GPS signal without inter- 
ruption due to the configuration of satellites, terrain and obsta- 
cles. Alternative navigation system had to be applied to avoid 
gaps from GPS signals. Alternative navigation system consists 
of angular sensors (heading, pitch, roll) and odometer. Angular 
sensors are combined in specially designed digital module. 
Digital module consists of three magnetoresistive magnetic sen- 
sors and a liquid filled two-axis tilt sensor to produce tilt com- 
pensated heading data. 
Design of used compass module ensures precise heading 
measurements up to 40 degrees. Digital magnetic compass is 
very sensitive on any disturbances of magnetic field. All 
magnetic compasses have to be calibrated in order to 
compensate for magnetic fields other than the earth's field 
components to get accurate heading. These additional magnetic 
fields are generated by the host and therefore depend on the 
compass mounting location. By performing a simple procedure, 
the digital compass module can compensate for steady, static 
220 
magnetic fields known as hard iron fields. Field components 
found after a calibration are only valid for the particular 
orientation and location of the compass. A re-calibration is 
necessary after a relocation of the compass or if the platform 
has changed its magnetic character. 
Compass calibration is performed by following a calibration 
procedure specified by the manufacturer. During this procedure 
the compass collects data required for the compensation algo- 
rithms. The goal of the calibration procedure is to sample the 
magnetic field components for many possible orientations of 
the host system. Rotating the host system through 360 degrees 
or driving in a circle (in the case of a vehicle) will enable the 
compass to sample its magnetic environment. 
2.3 Software 
Due to the specific needs of the project realisation there was no 
proper software to fit our demands. 
For thr exterior orientation of the video images we developed 
program Gladiator (Figure 3). The main tasks of the software 
are: 
e Checking and managing trajectory 
e Synchronisation of the GPS measurements with 
angular and odometer measurements 
e Synchronisation of the GPS measurements and video 
images 
e Calculating trajectory from angular and length 
measurements 
  
  
  
  
Figure 3. Data processing in Gladiator 
Video images were processed in the program VideoCar (Figure 
4). The main tasks of this program are: 
e Stereo and mono image data acquisition from video 
images 
e Road width measurements of 
e Object attributing 
e Database creation 
e Preparation of report forms 
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