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

Can Global Visual Features Improve Tag Recommendation for Image Annotation?

1,* , 2
 and 3
Received: 5 August 2010; in revised form: 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 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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.

AMA Style

Lux M, Pitman A, Marques O. Can Global Visual Features Improve Tag Recommendation for Image Annotation? Future Internet. 2010; 2(3):341-362.

Chicago/Turabian Style

Lux, Mathias; Pitman, Arthur; Marques, Oge. 2010. "Can Global Visual Features Improve Tag Recommendation for Image Annotation?" Future Internet 2, no. 3: 341-362.

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