Peculiar image search by Web-extracted appearance descriptions

Shun Hattori
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引用次数: 9

Abstract

We have become able to get enough approvable images of a target object just by submitting its object-name to a conventional keyword-based Web image search engine. However, because the search results rarely include its uncommon images, we can often get only its common images and cannot easily get exhaustive knowledge about its appearance (look and feel). As next steps of image searches in the Web, it is very important to discriminate between “Typical Images” and “Peculiar Images” in the approvable images, and moreover, to collect many different kinds of peculiar images as exhaustively as possible. This paper proposes a novel method to precisely retrieve peculiar images of a target object by its typical/peculiar appearance descriptions (e.g., color-names) extracted from the Web and/or its typical/peculiar image features (e.g., color-features) converted from them, as a solution to the 1st next step of image retrievals in the Web.
基于网络提取外观描述的特殊图像搜索
我们已经能够通过向传统的基于关键字的Web图像搜索引擎提交对象名称来获得足够多的目标对象的合格图像。然而,由于搜索结果很少包含它的不常见图像,我们往往只能得到它的常见图像,而不容易得到它的外观(外观和感觉)的详尽知识。作为网络图像搜索的下一步,区分“典型图像”和“特殊图像”是非常重要的,此外,尽可能详尽地收集各种不同类型的特殊图像。本文提出了一种新的方法,通过从网络中提取目标物体的典型/特殊外观描述(如颜色名称)和/或由其转换的典型/特殊图像特征(如颜色特征)来精确检索目标物体的特殊图像,作为网络图像检索的第一步的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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