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Capturing task knowledge for geo-spatial imagery

机译:捕获地理空间图像的任务知识

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Geo-spatial image databases are employed in a wide range of applications, such as intelligence operations, recreational and professional mapping, urban and industrial planning, and tourism systems. Effective retrieval of relevant images from such digital libraries can employ knowledge about what an image contains, why image contents are important in a particular domain, and how specific images have been used for particular domain tasks. Approaches to annotation for multimedia information retrieval have typically focused on the first two types of knowledge; however, managing the knowledge implicit in using geo-spatial imagery to address particular tasks can be crucial for capturing and making the most effective use of organisational knowledge assets. We are developing case-based knowledge-management support for large geo-spatial image repositories that scaffolds task-based knowledge capture about a content-based sketch query mechanism. This paper describes our task-centric approach to image annotation and retrieval, and it presents our initial implementation of the approach.
机译:地理空间图像数据库被广泛应用,例如情报操作,娱乐和专业制图,城市和工业规划以及旅游系统。从此类数字图书馆中有效检索相关图像可以利用以下知识:图像包含的内容,为什么图像的内容在特定领域中很重要以及如何使用>特定的映像已用于特定的域任务。用于多媒体信息检索的注释方法通常集中在前两种知识上。但是,管理使用地理空间图像解决特定任务时隐含的知识对于获取和最有效地利用组织知识资产至关重要。我们正在为大型地理空间图像存储库开发基于案例的知识管理支持,以支持有关基于内容的草图查询机制的基于任务的知识捕获。本文介绍了以任务为中心的图像标注和检索方法,并介绍了该方法的初始实现。

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