文章基本信息

标题：Can Global Visual Features Improve Tag Recommendation for Image Annotation?
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作者：Mathias Lux ; Arthur Pitman ; Oge Marques 等
期刊名称：Future Internet
电子版ISSN：1999-5903
出版年度：2010
卷号：2
期号：3
页码：341-362
出版社：MDPI Publishing
摘要：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.
关键词：image retrieval; multimedia; metadata; folksonomies; tagging; image annotation; tag recommendation; visual information retrieval