Shape Retrieval by Partially Supervised Fuzzy Clustering

DOI

10.2991/eusflat.2013.28How to use a DOI?

Keywords

Shape retrieval Fuzzy clustering Partially-supervised clustering

Abstract

In this work we propose the use of partially supervised fuzzy clustering to create a two-level indexing structure useful for enabling efficient shape retrieval. Similar shapes are grouped by a fuzzy clustering algorithm that embeds a partial supervision mechanism exploiting domain knowledge expressed in terms of a set of labeled shapes. After clustering, a set of prototypes representative of shape clusters is derived and used as indexing mechanism for retrieval. A shape query is matched against prototypes, instead of the whole shape database, and then shapes belonging to clusters for which prototype similarity is higher are returned. Experimental results obtained on two different datasets are presented to show the effectiveness of the proposed approach

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Giovanna Castellano
AU  - Anna Maria Fanelli
AU  - Maria Alessandra Torsello
PY  - 2013/08
DA  - 2013/08
TI  - Shape Retrieval by Partially Supervised Fuzzy Clustering
BT  - Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 195
EP  - 200
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.28
DO  - 10.2991/eusflat.2013.28
ID  - Castellano2013/08
ER  -