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Hierarchical image modeling for object-based media retrieval

机译:基于对象的媒体检索的分层图像建模

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摘要

Images are more structurally complex than the data stored in the traditional DBMSs. Many systems perform media retrieval based on image feature matching; the fact that images have structures is ignored. On the other hand, we view images as compound objects containing many component objects. Each component object corresponds to a region(s) that is a visually and semantically meaningful entity (e.g. car, man, etc.). As images/objects truly have hierarchical structures and have both visual and semantics properties, we argue that image retrieval using either semantics and image matching alone is insufficient. In this paper, we introduce a hierarchical structure for image modeling to support image retrieval using combinations of semantic expressions and visual examples at both the whole image and object levels. We give formal definitions of a multimedia query language and a system implementation based on this image modeling. We also address associated query processing issues and discuss the portability and extendibility of our approach.
机译:图像在结构上比传统DBMS中存储的数据更为复杂。许多系统都是基于图像特征匹配来进行媒体检索的。图像具有结构的事实被忽略。另一方面,我们将图像视为包含许多组成对象的复合对象。每个组成对象对应于一个区域,该区域是视觉上和语义上有意义的实体(例如汽车,人等)。由于图像/对象确实具有层次结构,并且具有视觉和语义属性,因此我们认为仅使用语义和图像匹配进行图像检索是不够的。在本文中,我们介绍了一种用于图像建模的层次结构,以在整个图像和对象级别使用语义表达和可视示例的组合来支持图像检索。我们给出了基于这种图像建模的多媒体查询语言和系统实现的正式定义。我们还将解决相关的查询处理问题,并讨论我们方法的可移植性和可扩展性。

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