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Linking text and visual concepts semantically for cross modal multimedia search

机译:用语义上与跨模型多媒体搜索一起链接文本和视觉概念

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Currently, popular search engines retrieve documents on the basis of text information. However, integrating the visual information with the text-based search for video and image retrieval is still a hot research topic. In this paper, we propose and evaluate a video search framework based on using visual information to enrich the classic text-based search for video retrieval. With the proposed framework, we endeavor to show experimentally, on a set of real world scenarios, that visual cues can effectively contribute to significant quality improvement of video retrieval. Experimental results show that mapping text-based queries to visual concepts improves the performance of the search system. Moreover, when appropriately selecting the relevant visual concepts for a query, a very substantial improvement of the system's performance is achieved.
机译:目前,流行的搜索引擎根据文本信息检索文档。 但是,将视觉信息与基于文本的搜索集成在一起视频和图像检索仍然是一个热门的研究主题。 在本文中,我们提出了基于使用可视信息来评估视频搜索框架,以丰富基于经典的基于文本的视频检索搜索。 通过拟议的框架,我们努力在实验上显示一套现实世界的情景,即视觉提示可以有效地促进视频检索的显着提高。 实验结果表明,将基于文本的查询映射到视觉概念提高了搜索系统的性能。 此外,当适当地选择查询的相关视觉概念时,实现了系统性能的非常大幅提高。

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