Automatic image annotation using visual content and folksonomies |
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Authors: | Stefanie Lindstaedt Roland Mörzinger Robert Sorschag Viktoria Pammer Georg Thallinger |
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Affiliation: | (1) Know-Center / KMI TU Graz, Inffeldgasse 21A, Graz, Austria;(2) Joanneum Research, Institute of Information Systems and Information Management, Steyrergasse 17, 8010 Graz, Austria |
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Abstract: | Automatic image annotation is an important and challenging task, and becomes increasingly necessary when managing large image collections. This paper describes techniques for automatic image annotation that take advantage of collaboratively annotated image databases, so called visual folksonomies. Our approach applies two techniques based on image analysis: First, classification annotates images with a controlled vocabulary and second tag propagation along visually similar images. The latter propagates 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. Both techniques were applied in the prototypical tag recommender “tagr”. |
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Keywords: | Auto-annotation Tagging Image retrieval Classification |
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