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Searching for semantic person queries using channel representations

机译:使用渠道表示搜索语义人查询

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It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.
机译:听到感兴趣的人的身高,身材和衣着(即类型和肤色)的描述并不少见。人们通常使用这些语义描述来描述其他事物,因为它们之间的联系迅速且易于理解。但是,这样的查询在智能监视系统中不容易利用,因为它们很难转换成可以在大型摄像机网络中自动搜索的表示形式。在本文中,我们提出了一种新颖的方法,该方法可将这种语义查询转换为可在视频流中搜索的化身,并演示基于描述的在视频中定位对象的最新性能。

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