Automatic Image Annotation using Visual Content and Folksonomies

Roland Mörzinger, Robert Sorschag, Georg Thallinger, Stefanie Lindstaedt

Abstract

Automatic image annotation is an important and challenging task when managing large image collections. This paper describes techniques for automatic image annotation by taking advantage of collaboratively annotated image databases, so called visual folksonomies. Our approach applies two techniques based on image analysis: Classification annotates images with a controlled vocabulary while tag propagation uses user generated, folksonomic annotations and is therefore capable of dealing with an unlimited vocabulary. Experiments with a pool of Flickr images demonstrate the high accuracy and efficiency of the proposed methods in the task of automatic image annotation.

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Paper Citation


in Harvard Style

Mörzinger R., Sorschag R., Thallinger G. and Lindstaedt S. (2008). Automatic Image Annotation using Visual Content and Folksonomies . In Metadata Mining for Image Understanding - Volume 1: MMIU, (VISIGRAPP 2008) ISBN 978-989-8111-24-1, pages 58-66. DOI: 10.5220/0002337600580066


in Bibtex Style

@conference{mmiu08,
author={Roland Mörzinger and Robert Sorschag and Georg Thallinger and Stefanie Lindstaedt},
title={Automatic Image Annotation using Visual Content and Folksonomies},
booktitle={Metadata Mining for Image Understanding - Volume 1: MMIU, (VISIGRAPP 2008)},
year={2008},
pages={58-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002337600580066},
isbn={978-989-8111-24-1},
}


in EndNote Style

TY - CONF
JO - Metadata Mining for Image Understanding - Volume 1: MMIU, (VISIGRAPP 2008)
TI - Automatic Image Annotation using Visual Content and Folksonomies
SN - 978-989-8111-24-1
AU - Mörzinger R.
AU - Sorschag R.
AU - Thallinger G.
AU - Lindstaedt S.
PY - 2008
SP - 58
EP - 66
DO - 10.5220/0002337600580066