The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3b. Beijing 2008
Figure 2: Illumination variation before failure in data set 1 (up)
and data set 2 (down). The left figures are the reference images
and the right ones are the candidate images. The difference
between the images is the transformation of the whole image
and illumination differences.
5. CONCLUSION
We have evaluated and quantified the robustness of our
stabilization method with respect to the amount of disturbances.
The disturbances were simulated as either moving objects or
illumination variation. The acceptance of our method is decided
based on acceptable parameter and geometric errors.
The simulation is done based on extreme case of illumination
variation and moving objects. The presented percentage of
amount of the disturbances can be increased in the case of
having illumination variations with non destructive nature or
moving object with low motion correlation.
More disturbances would be handled by having more structure
in the image. The results demonstrate the low percentage of
disturbances in the acceptance boundaries in an image with
almost no structure outside the road area and having a road in
the middle of the image. However the stabilization of this case
can be done without having a very high amount of disturbances.
This data set is an extreme case. In the other data set with
highway crossing, even a very high amount of the disturbances
in both moving objects and illumination variations provide
acceptable results. This case shows the robustness of our
method in handling very large disturbances which in reality
would not occur.
disturbances %
disturbances %
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disturbances %
Figure 3: Moving object boundaries
Data set 1 is represented in blue and data set 2 in red. The
acceptable percentage of the amount of the illumination
variation is represented by the star. The region between the star
and rectangle is the optimizer failure within our settings. The
circle shows one of the failure cases from this type. The area
after rectangle shows the real rejection. The method is robust
before the specific amount of moving objects which is indicated
by star. All the normalized parameter errors are also zero.