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Efficient tools for power annotation of visual contents

机译:高效的视觉内容标注工具

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摘要

Techniques for content-based image or video retrieval are not mature enough to recognize visual semantic completely. Whereas retrieval based on color, size, texture and shape are within the state of the art, our investigations on human factor analysis indicate that it is necessary to use captions or text annotations that are associated with photos and videos in content access of visual data. In this paper, a framework for integration of textual and visual content searching mechanism is presented. The framework includes ontology-based semantic query expansion, database navigation in a conceptual hierarchy, and a computational model for degree of term similarity calculation. The proposed method is embedded and evaluated in our novel content-based image database system called PicDB#8482;.

机译:

基于内容的图像或视频检索技术还不够成熟,无法完全识别视觉语义。尽管基于颜色,大小,纹理和形状的检索属于当前技术水平,但我们对人为因素分析的研究表明,在视觉数据的内容访问中,有必要使用与照片和视频相关联的标题或文本注释。本文提出了一种整合文本和视觉内容搜索机制的框架。该框架包括基于本体的语义查询扩展,概念层次结构中的数据库导航以及用于术语相似度计算的计算模型。将该方法嵌入到我们新颖的基于内容的图像数据库系统PicDB#8482;中并进行了评估。

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