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34th IAS International Meeting of Sedimentology, Rome, 10-13 September 2019. Field Trip - Guide Book
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Line-based object recognition using Hausdorff distance: from range images to molecular secondary structures
No full textObject recognition algorithms are fundamental tools in automatic
matching of geometric shapes within a background scene. Many approaches
have been proposed in the past to solve the object recognition
problem. Two of the key aspects that distinguish them in terms of
their practical usability are: (i) the type of input model description
and (ii) the comparison criteria used.
In this paper we introduce a novel scheme for 3D object recognition
based on line segment representation of the input shapes and comparison
using the Hausdorff distance. This choice of model representation
provides the flexibility to apply the scheme in different application areas.
We define several variants of the Hausdorff distance to compare
the models within the framework of well defined metric spaces.
We present a matching algorithm that efficiently finds a pattern in
a 3D scene. The algorithm approximates a minimization procedure of
the Hausdorff distance. The output error due to the approximation is
guaranteed to be within a known constant bound.
Practical results are presented for two classes of objects: (i) polyhedral
shapes extracted from segmented range images and (ii) secondary
structures of large molecules. In both cases the use of our
approximate algorithm allows to match correctly the pattern in the
background while achieving the efficiency necessary for practical use
of the scheme. In particular the performance is improved substantially
with minor degradation of the quality of the matching
T-shape cross walls strengthened by CFRP-sheets under combined compression and shear loading
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