多媒体检索中文本与视觉信息的语义组合

S. Clinchant, Julien Ah-Pine, G. Csurka
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引用次数: 103

摘要

本文的目标是引入一套我们称之为语义组合的技术,以便在多媒体信息访问的背景下有效地融合文本和图像检索系统。这些技术的出现是由于观察到图像和文本查询在不同的语义级别上表示,并且单个图像查询通常是不明确的。总的来说,语义组合技术克服了概念障碍而不是技术障碍:这些方法可以看作是后期融合和图像重排序的结合。这种方法虽然简单,但尚未被使用。我们使用4个不同的ImageCLEF数据集评估了针对后期和跨媒体融合的拟议技术。与后期融合相比,两个数据集的性能显著提高,而另外两个数据集的性能保持相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic combination of textual and visual information in multimedia retrieval
The goal of this paper is to introduce a set of techniques we call semantic combination in order to efficiently fuse text and image retrieval systems in the context of multimedia information access. These techniques emerge from the observation that image and textual queries are expressed at different semantic levels and that a single image query is often ambiguous. Overall, the semantic combination techniques overcome a conceptual barrier rather than a technical one: these methods can be seen as a combination of late fusion and image reranking. Albeit simple, this approach has not been used yet. We assess the proposed techniques against late and cross-media fusion using 4 different ImageCLEF datasets. Compared to late fusion, performances significantly increase on two datasets and remain similar on the two other ones.
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