Video Observations for Cloud Activity-Based Intelligence (VOCABI)

被引:0
|
作者
Blasch, Erik [1 ]
DiBona, Phillip [2 ]
Czajkowski, Michael [2 ]
Barry, Kevin [2 ]
Rimey, Ray
Freeman, Jeff
Newman, Kevin
Aved, Alex [1 ]
Hinman, Mike [1 ]
机构
[1] Air Force Res Lab, Rome, NY 13441 USA
[2] LM ATL INL, Cherry Hill, NJ 08002 USA
关键词
Video Analytics; Cloud Computing; automation and autonomy; information fusion; visualization; FUSION;
D O I
暂无
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The availability of video imagery through reduction in sensor size, cost, and power has enabled an explosion of collection opportunities. With the increased amount of imagery there is a need to understand the usefulness of video for applications such as Activity-Based Intelligence (ABI), situation understanding, and event-based processing. In this paper, we explore some of the emerging developments in video observations with a focus on cloud technology. Cloud technology supports integration of multiple algorithms, storage of large data sets, indexing over multimedia, and workflow opportunities between humans and machines. We highlight multiple tools such as GeoFlix (TM), Application Knowledge Interface To Algorithms (AKITA (TM)), and Intelligence Preparation of the Operational Environment (IPOE) using the Ozone Widget Framework (OWF) for permissive surveillance, data to decisions, and information fusion. These tools enable data analytics, algorithm comparison, and user-defined visualizations. An example is presented for target localization and tracking through planned video observations.
引用
收藏
页码:207 / 214
页数:8
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