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Using GPU-generated virtual video stream for multi-sensor system

机译:将GPU生成的虚拟视频流用于多传感器系统

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Security and intelligence services are increasingly turning toward multi-sensor video surveillance which requires human ability to successfully fuse and comprehend the information provided by videos. A training system using the same front end as real multi-sensor system for users can significantly increase such human ability. The training system always needs scenarios replicating stressful situations which are videotaped in advance and played later. This not only puts a limitation on the training scenarios but also brings a high cost. This paper introduces a new framework, virtual video capture device for such training system. Using the latest graphics processing units (GPUs) technology, multiple video streams composed of computer graphics (CG) are generated on one high-end PC and published to a video stream server. Thus users can be trained using both real video streams and virtual video streams on one system. It also enables the training system to use real video streams incorporating augmented reality to improve situation awareness of the human.
机译:安全和情报服务正越来越多地转向多传感器视频监视,这要求人类能够成功融合并理解视频提供的信息。为用户使用与真实的多传感器系统相同的前端的训练系统可以显着提高此类人员的能力。培训系统始终需要复制压力情景的场景,这些情景事先会被录像,然后再播放。这不仅限制了训练场景,而且带来了高昂的成本。本文介绍了一种用于此类训练系统的新框架,虚拟视频捕获设备。使用最新的图形处理单元(GPU)技术,在一台高端PC上生成由计算机图形(CG)组成的多个视频流,并将其发布到视频流服务器。因此,可以在一个系统上使用真实视频流和虚拟视频流来训练用户。它还使训练系统能够使用结合了增强现实的真实视频流来提高人们的处境意识。

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