| Authors |
Donoser Michael, Riemenschneider Hayko, Bischof Horst |
| Appeared in |
IPSJ Transactions on Computer Vision and Applications |
| Date |
2010 |
| Abstract |
This paper introduces a novel efficient partial shape matching
method named IS-Match. We use sampled points from the
silhouette as a shape representation. The sampled points can be
ordered which in turn allows to formulate the matching step as an
order-preserving assignment problem. We propose an angle descriptor
between shape chords combining the advantages of global and local
shape description. An efficient integral image based
implementation of the matching step is introduced which allows
detecting partial matches an order of magnitude faster than
comparable methods. We further show how the proposed algorithm is
used to calculate a global optimal Pareto frontier to define a
partial similarity measure between shapes. Shape retrieval
experiments on standard shape datasets like MPEG-7 prove that
state-of-the-art results are achieved at reduced computational
costs. |
| Link |
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