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Future Internet 2010, 2(3), 341-362; doi:10.3390/fi2030341

Can Global Visual Features Improve Tag Recommendation for Image Annotation?

1
Institute for Information Technology, Klagenfurt University, Universitaetsstr, 65-67, 9020 Klagenfurt, Austria
2
Institute for Applied Informatics, Klagenfurt University, Universitaetsstr, 65-67, 9020 Klagenfurt, Austria
3
Department of Computer & Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Rd, Boca Raton, FL 33431, USA
*
Author to whom correspondence should be addressed.
Received: 5 August 2010 / Revised: 21 August 2010 / Accepted: 26 August 2010 / Published: 27 August 2010
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Abstract

Recent advances in the fields of digital photography, networking and computing, have made it easier than ever for users to store and share photographs. However without sufficient metadata, e.g., in the form of tags, photos are difficult to find and organize. In this paper, we describe a system that recommends tags for image annotation. We postulate that the use of low-level global visual features can improve the quality of the tag recommendation process when compared to a baseline statistical method based on tag co-occurrence. We present results from experiments conducted using photos and metadata sourced from the Flickr photo website that suggest that the use of visual features improves the mean average precision (MAP) of the system and increases the system's ability to suggest different tags, therefore justifying the associated increase in complexity.
Keywords: image retrieval; multimedia; metadata; folksonomies; tagging; image annotation; tag recommendation; visual information retrieval image retrieval; multimedia; metadata; folksonomies; tagging; image annotation; tag recommendation; visual information retrieval
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Lux, M.; Pitman, A.; Marques, O. Can Global Visual Features Improve Tag Recommendation for Image Annotation? Future Internet 2010, 2, 341-362.

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