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5 CONCLUSIONS
One of the challenges of scene interpretation is the
use of structural information for improving the inter-
pretation of a scene. This paper describes an approach
for integrating two separate sources of structure and
shows that this combination improves the detection
of windows in the fac¸ade domain. The low-level
structure detector typically computes a large number
of potential primitive and structured evidences. A
middle-layer component called “Matchbox” reduces
this number by selecting the best primitives and struc-
tures. High-level reasoning creates hypotheses of
missing objects that are caused by the context of the
surrounding scene objects. These hypotheses are con-
firmed or refuted by comparing them to the low-level
results. Thus, the Matchbox mediates between both
sources of structures, and relates high-level concepts
to low-level detections.
The approach was tested on a set of fac¸ade im-
ages, which are rich in structure. The results show
that combining visual and compositional structure can
considerably improve the detection of windows in
this domain compared to pure bottom-up approach
based on visual structure alone. Not all the correct
high-level hypotheses were confirmed by low-level
evidence, mostly due to poor contrast and partially
occluded windows. Further improvements might be
possible by using additional low-level detectors for
confirming or refuting high-level hypotheses.
ACKNOWLEDGEMENTS
This research has been supported by the European
Community under the grant IST 027113, eTRIMS
- eTraining for Interpreting Images of Man-Made
Scenes.
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