EuroSDR Projects - Host Ireland

load nor response time for anybody interested in the evaluation results, the idea is to set up a web
service to which one sends the results and gets back the evaluation.
Finally, we see promising directions for future research such as appearance based approaches, e.g,
(Leibe and Schiele 2004), which might not be so easily adapted for roads themselves, but which have
shown good results for cars, defining roads particularly in urban areas. Even more interesting might be
statistical generative modeling. A particularly impressive example is (Dick et al. 2004) for buildings,
but Stoica et al. (2004) have employed it for roads. To our knowledge this is the first time that the
natural variability of the road network has been modeled in a realistic way. This is of big importance
as the modeling of the network topology including the detailed characteristics of crossings is an area
where not much research has been conducted.
Additional remarks: One of the reviewers of the report sees a trend for the NMCAs in the acquisition
of very high resolution aerial imagery in the decimeter range. From it, highly detailed information
including separate lanes and road marks could be acquired with very short update cycles. For this, a
high degree of automation would be the only way to proceed. We agree with this, but note that we are
not aware of any research on road extraction focused on this type of imagery at the moment.
A reviewer of (Mayer et al. 2006) pointed on several issues not discussed so far which should be taken
into account for a follow up of the test. One issue is certainly how much parameters are allowed to be
tuned. Particularly for smaller image sizes optimal sets of parameters might be more important than
the approach applied. On the other hand, the images are fairly different and a single set of parameters
might lead to very unfavorable results. An issues closely linked to this is if the ground truth is given
out to the participants, possibly together with the code used for evaluation. This can on the one hand
be used by the participants to find out about good parameter settings but also strategies by running
multiple trials. On the other hand it can lead to approaches that just perform well for the given couple
of images. Depending on the state of the field both issues have their pros and cons. Concerning the
ranking it was proposed to have one official criterion (the geometric mean of completeness and
correctness is one, although it needs to be discussed further) for overall ranking, but to also give the
user the possibility to see the ranking according to individual criteria, such as completeness.
7 Acknowledgments
We want to thank Stefan Hinz as well as the EuroSDR reviewers Nicolas Paparoditis and Kevin
Mooney for their helpful comments and for improving the English of this report. We are grateful to
the reviewers of (Mayer et al. 2006) for valuable improvements of a shortened version of this report.
We finally would like to thank the Swiss Federal Office of Topography, Bern, Switzerland, Leica
Geosystems, Heerbrugg, Switzerland, and the Bundeswehr Geoinformation Office (AGeoBw),
Euskirchen, Germany, for making available the data for this test.
References
Bacher, U. and Mayer, H. (2004): Automatic Road Extraction from IRS Satellite Images in
Agricultural and Desert Areas, The International Archives of the Photogrammetry, Remote Sensing
and Spatial Information Sciences (35) B3, 1055-1060.
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