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首页> 外文期刊>Journal of Imaging Science and Technology >AssisTag: Seamless Integration of Content-based and Keyword-based Image Exploration for Category Search
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AssisTag: Seamless Integration of Content-based and Keyword-based Image Exploration for Category Search

机译:AssisTag:基于内容和基于关键字的图像探索的无缝集成,用于类别搜索

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摘要

Category search is a searching activity where the user has an example image and searches for other images of the same category. This activity often requires appropriate keywords of target categories making it difficult to search images without prior knowledge of appropriate keywords. Text annotations attached to images are a valuable resource for helping users to find appropriate keywords for the target categories. We propose an image exploration system in this article for category image search without the prior knowledge of category keywords. Our system integrates content-based and keyword-based image exploration and seamlessly switches exploration types according to user interests. The system enables users to learn target categories both in image and keyword representation through exploration activities. Our user study demonstrated the effectiveness of image exploration using our system, especially for the search of images with unfamiliar category compared to the single-modality image search. (C) 2016 Society for Imaging Science and Technology.
机译:类别搜索是一种搜索活动,其中用户拥有示例图像并搜索相同类别的其他图像。该活动通常需要目标类别的适当关键字,从而在没有适当关键字的先验知识的情况下很难搜索图像。图像上的文本注释是宝贵的资源,可帮助用户找到目标类别的适当关键字。我们在本文中提出了一种用于类别图像搜索的图像浏览系统,而无需类别关键字的先验知识。我们的系统集成了基于内容和基于关键字的图像探索,并根据用户兴趣无缝切换了探索类型。该系统使用户可以通过探索活动来学习图像和关键字表示形式中的目标类别。我们的用户研究证明了使用我们的系统进行图像探索的有效性,尤其是与单模态图像搜索相比,对于不熟悉类别的图像搜索。 (C)2016年影像科学与技术学会。

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