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Invited paper: Embedded face and biometric technologies for national and border security

机译:邀请纸:国家和边境安全的嵌入式面部和生物识别技术

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The CCTV surveillance industry is undergoing a sea change due to the adoption of IP technologies. This is allowing the integration of a plethora of new cameras and other sensors into huge integrated networks. Adoption of IP technologies is presenting opportunities for scalable visual analytics that has the potential to add enormous value to entire camera networks. One such technology is scalable robust face search to identify persons of interest in large crowds. Not only are such systems required to work robustly in a wide variety of conditions, they must also be extremely fast and scalable to hundreds, if not thousands, of high definition camera nodes. Developing and testing such technology is challenging and requires a combination of fast algorithms, distributed databases, mobile platform integration, parallel processing using distributed middleware such as ROS, and GPU acceleration using tools such as CUDA and OpenCL. In this paper we cover emerging system trends such as super-megapixel cameras, post incident digital PTZ, integration and fusion of video and non-video sensors, multimodal remote biometrics including face and iris on the move. Finally, recognition results will be presented from a formal face recognition trial in early 2011 in one of Asia's largest International airports.
机译:由于采用知识产权技术,中央电视台监控产业正在发生海洋变革。这是允许将多孔的新摄像机和其他传感器集成到巨大的集成网络中。采用IP技术正在为可扩展的视觉分析提供机会,这些分析有可能为整个相机网络增加巨大价值。一种这样的技术是可扩展的强大的脸部搜索,以识别大众人群的兴趣人物。不仅需要在各种条件下稳健地工作所需的系统,它们也必须非常快速且可扩展到数百个,如果不是数千个高清摄像机节点。开发和测试此类技术具有具有挑战性,并且需要使用快速算法,分布式数据库,移动平台集成,并行处理使用诸如ROS等分布式中间件的并行处理,以及使用CUDA和OpenCL等工具的GPU加速。在本文中,我们涵盖了新兴系统趋势,如超级百万像素摄像头,发布的数字PTZ,视频和非视频传感器的集成和融合,包括脸部和虹膜的多模式远程生物识别技术。最后,将从2011年初在亚洲最大的国际机场之一的正式面部识别试验中提出了认可结果。

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