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Scale invariant and
deformation tolerant partial shape matching |
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Brief description We present a novel approach to the problem of establishing the best
match between an open contour and a part of a closed contour. At the heart of
the proposed scheme lies a novel shape descriptor that also permits the
quantification of local scale. Shape descriptors are computed along open or
closed contours in a spatially non-uniform manner. The resulting ordered
collections of shape descriptors constitute the global shape representation.
A variant of an existing DTW matching technique is proposed to handle the
matching of shape representations. Due to the properties of the employed
shape descriptor, sampling scheme and matching procedure, the proposed
approach performs partial shape matching that is invariant to Euclidean
transformations, starting point as well as to considerable shape
deformations. Additionally, the problem of matching closed-to-closed contours
is naturally treated as a special case. Extensive experiments on benchmark
datasets but also in the context of specific applications, demonstrate that
the proposed scheme outperforms existing methods for the problem of partial
shape matching and performs comparably to methods for full shape matching. Sample results
Download video showing human
upper body detection, as an application of the proposed partial shape
matching method. The video is compiled with the xvid
MPEG4 codec.
Download video showing hand
posture recognition, as an application of the proposed partial shape matching
method. The video is compiled with the xvid MPEG4
codec. Follow this link to see the
results of the proposed method on the exhaustive MPEG7 shape classification
experiment. The first shape in each line is a query shape. The rest 40 shapes
are those retrieved by the proposed method in the order of decreasing
similarity. There exist 1400 rows, one for each of the 1400 shapes of the
MPEG7 dataset. A red vertical line separates the first 20 matches from the
rest, since in the MPEG7 dataset, there exist 20
shapes in each shape class. Matches have been obtained before the application
of graph transduction (GT), so that the merit of the proposed method can be
assessed without the improvement introduced by GT. Contributors Michel Damien, Iasonas
Oikonomidis, Antonis Argyros. This
work was partially supported by the IST-FP7-IP-215821 project GRASP. Relevant publications ·
D. Michel, I. Oikonomidis, A.A. Argyros, “Scale invariant and
deformation tolerant partial shape matching”, to appear in Image and Vision Computing Journal, Elsevier. The
electronic versions of the above publications can be downloaded from my publications page. |
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Last update: |
30 January 2011, Antonis Argyros, argyros@ics.forth.gr |
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