B. Matching
As shown in [7] several methods exist for analyzing the
translation between consecutive images. If feature points are
extracted, then some kind of matching algorithm is required
to calculate translation. In [12] Harris corners are extracted
and in the matching are performed with normalized cross
correlation over an 11x11 pixel neighborhood. Usually
normalized cross correlation is used on small regions. Two
reasons are less computational cost and fewer problems
caused by different projections of the images. The
perpendicular mounting of the cameras and selection of a
lens with low distortion reduces these problems.
Since normalized cross correlation can provide a measure
of traveled distance directly without any feature extraction,
this method is selected. Sub-pixel accuracy is obtained by
fitting a paraboloid to the peak in the similarity image [13].
First similarity between the stereo pair is calculated to obtain
the height and then between two consecutive images of the
left camera to obtain the translation. Fig. 3 shows how the
disparities are calculated.