DocumentCode :
1799695
Title :
An image community detection method for hierarchical visualisation
Author :
Esen, Ersin ; Ozkan, Savas ; Atil, I. ; Arabaci, M.A. ; Tankiz, Seda
Author_Institution :
TUBITAK UZAY, Turkey
fYear :
2014
fDate :
14-18 July 2014
Firstpage :
1
Lastpage :
6
Abstract :
Better ways of representing the results of image search can be found rather than regular lists of thumbnails. For this purpose, we propose a hierarchical visualisation scheme with two stages. We utilise the notion of image community and aim to detect communities within a large set of images by means of a novel deterministic community detection method. After image communities are detected, the representative key images of these communities are presented to the user in an intuitive and expressive layout. The layout is determined according to the detected community structure. As a result, the user is presented a distinctive set of images at the first stage. If similar images are desired, the members of the communities can be explored at the second stage. We experimentally show that the proposed community detection algorithm significantly outperforms generic community detection methods. Furthermore, we believe that the proposed hierarchical visualisation can be preferred by many of the users.
Keywords :
data visualisation; image retrieval; object detection; deterministic community detection method; expressive layout; hierarchical visualisation; image community detection method; image search; intuitive layout; Communities; Equations; Image edge detection; Indexes; Layout; Measurement; Visualization; Image graph; hierarchical visualisation; image community;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo Workshops (ICMEW), 2014 IEEE International Conference on
Conference_Location :
Chengdu
ISSN :
1945-7871
Type :
conf
DOI :
10.1109/ICMEW.2014.6890710
Filename :
6890710
Link To Document :
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