Video content analysis with effective response

被引：4

作者：

Abrams, David ^{[1
]}

McDowall, Steven ^{[2
]}

机构：

[1] TrueSentry, 111 N Chestnut St,Suite 200, Winston Salem, NC 27101 USA

[2] Interact Publ Safety Syst, Winston Salem, NC 27101 USA

来源：

2007 IEEE CONFERENCE ON TECHNOLOGIES FOR HOMELAND SECURITY: ENHANCING CRITICAL INFRASTRUCTURE DEPENDABILITY | 2007年

关键词：

computer vision; tracking; video surveillance; collaboration; notification; command centers;

D O I：

10.1109/THS.2007.370020

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 [检测技术与自动化装置]; 0816 [测绘科学与技术]; 081602 [摄影测量与遥感]; 083002 [环境工程]; 1404 [遥感科学与技术];

摘要：

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.

引用

页码：57 / +

页数：2

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