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A Method for Evaluating the Performance of Content-Based Image Retrieval Systems Based on Subjectively Determined Similarity between Images

机译:基于主观确定图像间相似度的基于内容的图像检索系统性能评估方法

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In recent years multimedia researchers have attempted to design content-based image retrieval systems. However, despite the development of these systems, the term "content" has still remained rather ill defined, and this has made the evaluation of such systems problematic. This paper proposes a method for the creation of a reference image set in which the similarity of each image pair is estimated by two independent methods - by the subjective evaluation of human observers, and by the use of "visual content words" as basis vectors that allow the multidimensional content of each image to be represented with a content vector. The similarity measure computed with these content vectors is shown to correlate with the subjective judgment of human observers, and thus provides both a more objective method for evaluating and expressing image content, and a possible path to automating the process of content-based indexing in the future.
机译:近年来,多媒体研究人员已尝试设计基于内容的图像检索系统。但是,尽管开发了这些系统,但是术语“内容”仍然定义不清,这使得对这样的系统的评估成为问题。本文提出了一种创建参考图像集的方法,其中,通过两种独立的方法估算每个图像对的相似性-通过对人类观察者的主观评估,以及通过使用“视觉内容词”作为基础向量,允许使用内容向量表示每个图像的多维内容。用这些内容向量计算出的相似性度量显示出与人类观察者的主观判断相关,从而为评估和表达图像内容提供了一种更为客观的方法,并为自动化基于内容的索引过程提供了一条可能的途径。未来。

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