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首页> 外文会议>Conference on Storage and Retrieval for Media Databases 2001 Jan 24-26, 2001, San Jose, USA >Mapping low-level image features to semantic concepts
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Mapping low-level image features to semantic concepts

机译：将低级图像特征映射到语义概念

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摘要

Humans tend to use high-level semantic concepts when querying and browsing multimedia databases; there is thus, a need for systems that extract these concepts and make available annotations for the multimedia data. The system presented in this paper satisfies this need by automatically generating semantic concepts for images from their low-level visual features. The proposed system is built in two stages. First, an adaptation of k-means clustering using a non-Euclidean similarity metric is applied to discover the natural patterns of the data in the low-level feature space; the cluster prototype is designed to summarize the cluster in a manner that is suited for quick human comprehension of its components. Second, statistics measuring the variation within each cluster are used to derive a set of mappings between the most significant low-level features and the most frequent keywords of the corresponding cluster. The set of the derived rules could be used further to capture the semantic content and index new untagged images added to the image database. The attachment of semantic concepts to images will also give the system the advantage of handling queries expressed in terms of keywords and thus, it reduces the semantic gap between the user's conceptualization of a query and the query that is actually specified to the system. While the suggested scheme works with any kind of low-level features, our implementation and description of the system is centered on the use of image color information. Experiments using a 21 00 image database are presented to show the efficacy of the proposed system.
机译：人们在查询和浏览多媒体数据库时倾向于使用高级语义概念。因此，需要提取这些概念并为多媒体数据提供可用注释的系统。本文提出的系统通过自动从图像的低层视觉特征生成图像的语义概念来满足此需求。拟议的系统分为两个阶段。首先，使用非欧几里得相似性度量对k均值聚类进行自适应，以发现低层特征空间中数据的自然模式；集群原型旨在以适合人类快速了解其组件的方式来汇总集群。其次，使用测量每个群集内变化的统计信息来得出对应群集的最重要的低级功能和最频繁的关键字之间的一组映射。该组导出规则可以进一步用于捕获语义内容并索引添加到图像数据库的新的未标记图像。将语义概念附加到图像还将使系统具有处理用关键字表示的查询的优势，因此，它减少了用户对查询的概念化与系统实际指定的查询之间的语义鸿沟。虽然建议的方案可用于任何类型的低级功能，但我们对系统的实现和说明均以使用图像颜色信息为中心。提出了使用21 00图像数据库的实验，以显示所提出系统的功效。

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