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• Calculation of x”, y” image coordinates for the PTZ-
camera with the collinearity equation and initial
exterior orientation parameters.
• Calculation of rotation angles a and p with
a = atan(x”/ c) and P = atan(y” /c).
plane.
3.4 Analysis of high-resolution images
The high-resolution images are stored with time and position
stamps. A unique assignment of the attributes to the trajectories
is feasible, because of the observation of stand-alone
pedestrians. Since there is no automatic classification
implemented up to now, the pedestrians are interactively
classified by a human operator.
4. OUTLOOK
The two-camera system presented in this work is an essential
component for the assessment of the quality of shop-locations
in inner cities, since it delivers both the trajectories of the
pedestrians and information about additional attributes. So far,
the project is just in its starting phase. Actual investigations
concentrate on the improvement of speed and accuracy of the
control for the exterior orientation and on the zoom-control of
the PTZ-camera. This will improve the reliability of the
assignment of the classified pedestrians to their trajectories.
Furthermore the choice of a person from a number of detected
individuals up to now is arbitrary. A knowledge-based camera
control system will ensure the single acquisition of each
individual or the multiple acquisition of the same person if
wanted.
Future work will investigate the opportunity for automatic
classification of the pedestrians in the high-resolution images.
For this purpose different classifiers (e.g., AdaBoost, SVM)
will be evaluated. A training data set is gained by acquisition of
the high-resolution images.
The integration of a complete 3D-model of the scene allows an
improved modelling of the behaviour of pedestrians at obstacles
or in case of occlusions. Moreover motion models that specify
the probability for a change in direction or speed at certain
position will be integrated.
ACKNOWLEDGEMENT
Part of the work presented here was carried out in a student
research project by (in alphabetical order): Jonas Bostelmann,
Steven Piorun, Falko Schindler, Axel Schnitger, Aiko Sukdolak,
Martin Wiedeking,
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