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Empirical comparison of image retrieval color similarity methods with human judgment

机译:图像检索颜色相似度方法与人类判断的经验比较

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摘要

It is important to verify assumptions and methods of image retrieval against actual human behavior. A study was conducted to compare similarity methods of color histograms against human assessment of similarity. The similarity methods tested include basic histogram intersection, center histogram matching, locality histogram matching, and size-weighted histogram matching. 161 subjects participated in the empirical study. The findings, based on Spearman correlation analysis, showed that both the basic histogram intersection method and size-weighted histogram are very close to human assessment of similarity (Spearman correlation coefficient of 0.915). The other two are not close to human judgment on similarity. This study illustrates an alternative approach to evaluating matching algorithms. Unlike the usual measures of recall and precision, this approach emphasizes human validation. Fewer images are required with the use of statistical testing.
机译:重要的是对照实际的人类行为来验证图像检索的假设和方法。进行了一项研究,以比较颜色直方图的相似性方法与人类对相似性的评估。测试的相似性方法包括基本直方图交集,中心直方图匹配,位置直方图匹配和大小加权直方图匹配。 161名受试者参加了实证研究。基于Spearman相关分析的结果表明,基本直方图交集方法和大小加权直方图都非常接近人类对相似性的评估(Spearman相关系数为0.915)。另外两个与人类对相似性的判断并不接近。这项研究说明了评估匹配算法的另一种方法。与通常的召回率和精确度不同,此方法强调人工验证。使用统计测试所需的图像更少。

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