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Contact: Remco Veltkamp
Due to the recent improvements in laser scanning technology,
3D visualization and modelling,
there is an increasing need for tools supporting the automatic search for
3D objects in archives.
We have implemented a new geometric approach to
3D shape comparison and retrieval for arbitrary objects
described by 3D polyhedral models that may contain gaps.
To compare two objects geometrically we first apply
principal components analysis to bring the objects in a standard pose,
and enclose each object by a 3D grid.
Then we generate for each object a signature representing a weighted point set,
that contains for each non-empty grid cell a salient point.
We implemented three methods to select in each grid cell a salient point:
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(Gaussian curvature) choose the vertex in the cell with the highest Gaussian curvature, and
choose as weight a measure for that curvature,
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(Normal variation) choose the area-weighted mean of the vertices in the cell, and choose as
weight a measure denoting the normal variation of the faces in the cell and
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(Midpoint) choose the midpoint of all vertices in the cell, and choose as weight one.
Finally, we compute the similarity between two shapes by computing a new
transportation distance between the two weighted point sets that, unlike the
Earth Mover's Distance, satisfies the triangle inequality.
This property makes it suitable for use in indexing very large collections of
models.
To demonstrate the strength of our approach we implemented an experimental shape
retrieval engine. The results below are obtained using
- a database from Princeton
(133 models collected from
the web, as used in the paper "Matching 3D Models with Shape Distributions",
by Rob Osada et al., International Conference on Shape Modeling and Applications (SMI 2001)
- a database consisting of 684 VRML models,
that we have collected from the word wide web
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a database consisting of 102 "L-shaped" blocks that we have downloaded from the
ShapeSearch.net website.
The demo pages below use the VRML format to show the query model and the retrieved 3D models.
It is also possible to compare the weighted point sets of the query model and a retrievel model in VRML format.
You need a plugin
to view these VRML models, for example
cortona.
From our database containing 684 models we obtained a test database by classifying 512 models into six categories:
242 conventional air planes, 60 delta-jets, 45 multi-fuselages, 19 biplanes,
10 helicopters and 136 other models.
This classification was purely on the basis of shape, not on the type of
object.
We did not classify the remaining 172 models, because it was not clear to
which class these models should belong, looking at their shape.
You may download here, the test database and
our complete database.
The 'Princeton database' was kindly provided by the Princeton Shape Retrieval and Analysis Group.
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