Boosting image retrieval through aggregating search results based on visual annotations
Boosting image retrieval through aggregating search results based on visual annotations
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DOI：
10.1145/1459359.1459386
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发表时间：
2008-10
期刊：
影响因子：
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通讯作者：
Ximena Olivares;Massimiliano Ciaramita;R. V. Zwol
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文献类型：
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作者：
Ximena Olivares;Massimiliano Ciaramita;R. V. Zwol
在线照片共享系统（例如 Flickr 和 Picasa）提供了人工注释照片的宝贵来源。文本注释不仅用于描述图像的视觉内容，还用于描述主观、空间、时间和社会维度，使基于关键字的搜索任务变得复杂。在本文中，我们研究了一种利用视觉注释的方法，例如Flickr 中的注释，以增强基于关键字的系统检索性能。为此，我们采用基于内容的图像检索的视觉词袋方法作为我们的基线。然后，我们应用通过一组与基于关键字的查询匹配的视觉注释获得的前 25 个结果的排名聚合。检索实验的结果表明，将聚合方法与我们的基线进行比较时，检索性能显着提高，这也稍微优于纯文本搜索。当在搜索空间上使用文本过滤器并结合聚合方法时，可以观察到检索性能的额外提升，这强调了需要大规模基于内容的图像检索技术来补充基于文本的搜索。
Online photo sharing systems, such as Flickr and Picasa, provide a valuable source of human-annotated photos. Textual annotations are used not only to describe the visual content of an image, but also subjective, spatial, temporal and social dimensions, complicating the task of keyword-based search. In this paper we investigate a method that exploits visual annotations, e.g. notes in Flickr, to enhance keyword-based systems retrieval performance. For this purpose we adopt the bag-of-visual-words approach for content-based image retrieval as our baseline. We then apply rank aggregation of the top 25 results obtained with a set of visual annotations that match the keyword-based query. The results on retrieval experiments show significant improvements in retrieval performance when comparing the aggregated approach with our baseline, which also slightly outperforms text-only search. When using a textual filter on the search space in combination with the aggregated approach an additional boost in retrieval performance is observed, which underlines the need for large scale content-based image retrieval techniques to complement the text-based search.