Capturing contextual relationship for effective media search
Capturing contextual relationship for effective media search
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DOI：
10.1007/s11042-010-0670-4
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发表时间：
2009-12
影响因子：
3.6
通讯作者：
Guang-Ho Cha
中科院分区：
文献类型：
--
作者：
Guang-Ho Cha
媒体搜索的核心问题之一是根据媒体数据自动计算的低级特征与人类对其的解释之间的语义差距。这是因为相似性的概念通常基于高级抽象，但低级特征有时并不反映人类的感知。在本文中，我们假设媒体的语义是由数据集中的上下文关系决定的，并介绍了从大型媒体（尤其是图像）数据集中捕获上下文信息以进行有效搜索的方法。基于上下文信息的图像数据库中的相似性搜索显示出令人鼓舞的实验结果。
One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. In this paper, we assume the semantics of media is determined by thecontextualrelationship in a dataset, and introduce the method to capture the contextual information from a large media (especially image) dataset for effective search. Similarity search in an image database based on this contextual information shows encouraging experimental results.