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首页> 外文期刊>Journal of Multimedia >From Text to Images: Weighting Schemes for Image Retrieval
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From Text to Images: Weighting Schemes for Image Retrieval

机译：从文本到图像：图像检索的加权方案

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摘要

Bags of visual words are the most studied image description technique in the last years. This representation of images raised new possibilities as well as new research issues. In particular, it is important to automatically determine which visual words are the most relevant to describe the images, and which ones should be ignored. This issue is a classical problem of textual information retrieval, usually addressed by the use of weighting schemes. In this paper, the most common weighting schemes from text retrieval are applied to the case of visual word-based retrieval. New weighting schemes are also proposed, and several Minkowski-like distances are tested. The experiments are performed on four different datasets that correspond to two different retrieval tasks; it allows us to bring to light some properties of visual words and weighting schemes. This study results in several findings. It first shows that the optimal setting for distances and weighting schemes depends on the nature of the visual content of the images considered. Especially, raw frequency can be the most effective weight when dealing with complex datasets; it questions the habit to systematically use the tf. idf weighting scheme. It also shows that weighting schemes and Minkowski distances have similar effect and should be used together in a consistent way. Based on these findings, general guidelines for the choice of distances and weighting schemes are proposed.
机译：视觉单词袋是近年来研究最多的图像描述技术。图像的这种表示提出了新的可能性以及新的研究问题。尤其重要的是，自动确定哪些视觉词与描述图像最相关，哪些视觉词应被忽略。这个问题是文本信息检索的经典问题，通常通过使用加权方案来解决。本文将基于文本检索的最常见加权方案应用于基于视觉单词的检索。还提出了新的加权方案，并测试了多个类似Minkowski的距离。实验是在对应于两个不同检索任务的四个不同数据集上进行的；它使我们能够发现视觉单词和加权方案的某些属性。这项研究得出了一些发现。首先显示距离和加权方案的最佳设置取决于所考虑图像的视觉内容的性质。特别是在处理复杂数据集时，原始频率可能是最有效的权重。它质疑系统地使用tf的习惯。 idf加权方案。它还表明，加权方案和Minkowski距离具有相似的效果，应以一致的方式一起使用。基于这些发现，提出了选择距离和加权方案的一般准则。

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