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Multi-Camera Video Scene Graphs for Surveillance Videos Indexing and Retrieval

机译:用于监视视频索引和检索的多摄像机视频场景图

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Modern video surveillance systems often consist of multiple cameras capturing continuous videos. However, existing systems do not fully take advantage of shared scene semantics across multiple video streams, and hence querying the captured videos to find an event or object of interest can be a time-consuming task. In this paper, we propose a compact representation of objects and their relationships in the scene under surveillance, over time, and across multiple cameras, using a combined global spatio-temporal scene graph. The same objects that appear in multiple cameras are stored only once, reducing the storage required and speeding up the query when compared to storing the scene graph from each camera individually. Our experiments show that in a 5-camera system our proposed representation can speed up querying time by a factor of 3.9 times.
机译:现代视频监控系统通常包括多个摄像机捕获连续视频。 但是,现有系统无法完全利用多个视频流的共享场景语义,因此查询捕获的视频以查找感兴趣的事件或对象可以是耗时的任务。 在本文中,我们使用组合的全局时空场景图提出了在监视下,随着时间的推移和多个摄像机的场景中对象的紧凑表示及其关系。 在多个摄像机中显示的相同对象仅存储一次,减少所需的存储和加速查询,与单独从每个摄像机存储每个摄像机时。 我们的实验表明,在一个5相机系统中,我们所提出的表示可以加速查询时间为3.9倍。

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