Video Content Analysis with Effective Response

D. Abrams, S. McDowall
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引用次数: 6

Abstract

Video content analytics effectively identifies threats in video surveillance camera feeds. These behaviors include person/vehicle entering restricted zone, counter-flow detection, loitering, object left behind, and others. In order to provide enhanced security, events need to be integrated with a command and control system capable of effectively responding to hundreds of events per day in a busy, critical infrastructure facility. We describe a novel system -NerveCenter - that links analytic events with command center data wall camera pop-ups on alarm, extended notification tools that send multi-modal alerts, acknowledgement tracking, 911 computer aided dispatch (CAD), and geo-coded mapping tools that give operators a tactical map. The usability of these tools is discussed along with how to provide situational awareness and a common operating picture to operators and first responders.
视频内容分析与有效响应
视频内容分析有效地识别视频监控摄像机馈送中的威胁。这些行为包括人/车辆进入禁区、逆流检测、徘徊、遗留物品等。为了提供增强的安全性,需要将事件与能够在繁忙的关键基础设施中每天有效响应数百个事件的指挥和控制系统集成。我们描述了一种新颖的系统——nervecenter——它将分析事件与指挥中心数据墙报警时弹出的摄像头、发送多模态警报的扩展通知工具、确认跟踪、911计算机辅助调度(CAD)以及为操作员提供战术地图的地理编码制图工具联系起来。讨论了这些工具的可用性,以及如何为操作员和第一响应者提供态势感知和通用操作图像。
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