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Automatic Image Annotation using Visual Content and Folksonomies

Topics: Feature Extraction; Object, Event and Scene Recognition, Retrieval and Indexing; Pattern Recognition in Image Understanding; Recognition and Indexing; Statistical Approach

In Metadata Mining for Image Understanding - Volume 0VISIGRAPP, 58-66, 2008 , Funchal, Madeira, Portugal

Authors: Roland Mörzinger 1 ; Robert Sorschag 1 ; Georg Thallinger 1 and Stefanie Lindstaedt 2

Affiliations: 1 Joanneum Research, Institute of Information Systems and Information Management, Austria ; 2 Know-Center, Austria

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Feature Extraction ; Features Extraction ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing ; Statistical Approach

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

@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 (VISIGRAPP 2008) - MMIU},
year={2008},
pages={58-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002337600580066},
isbn={978-989-8111-24-1},
}

TY - CONF

JO - Metadata Mining for Image Understanding (VISIGRAPP 2008) - MMIU
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
PB - SciTePress

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