Since the processing is based on stereo vision, camera calibration plays a basic role for the
success of the approach.
It is divided in two steps.
- Supervised calibration:
the first part of the calibration process is an interactive step:
a grid with known size (figure 1.a)
painted onto the ground and
two stereo images (figure 1.b and 1.c) are captured and
used for the calibration.
Thanks to an X-Window based graphical interface
a user selects the intersections of the grid lines
using a mouse;
these intersections represent a small set of homologous points whose
world coordinates are known to the system;
this mapping is used to compute the calibration
The set of homologous points is used
to minimize different cost functions, such as, the distance between each
point and its neighbors and line parallelism.
This first step is intended to be performed only once when
the orientation of the cameras or the vehicle trim have changed.
Since the set of homologous points is small and their coordinates
may be affected by human imprecision,
this calibration represents
only a rough guess of the parameters, and
a further process is required.
- Automatic parameters tuning:
after the supervised phase, the computed calibration parameters
have to be refined. Moreover small changes in the vision system setup
or in the vehicle trim require a periodic tuning of the calibration.
For this purpose an automatic tool has been developed .
Since this step is only a refinement,
a structured environment, such as the grid, is no more required and
a mere flat road in front of the vision system suffices.
The parameters tuning consists of an iterative procedure
based on the application of the IPM transform to stereo images
(see the extension of IPM to stereo vision) and takes about 20 seconds.
Figure 1: (a) the segment of road used for calibration; (b) and (c) left and
right views of the calibration grid from ARGO's stereo cameras