一种智能视频监控框架

F. Ekpar
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引用次数: 7

摘要

本文提出了一种智能视频监控框架。强大的失真校正和渲染算法允许系统支持广泛的视频流源,包括360度全景视频系统,并促进视频流源的替代,从而提高可扩展性。在渐进式训练配置中采用自适应目标检测、分类和跟踪算法,使系统能够从以前的错误中学习,并随着使用的增加而提高性能。多个视频流源可以与任意形状的覆盖表面相结合,设计用于覆盖全球/局部地图上的空间分辨和定位检测和跟踪对象,例如全球定位系统(GPS)支持的监控场景地图,以大大提高态势感知能力。该系统的另一个独特功能是通过控制单元在覆盖表面和系统其余部分之间结合双向通信,从而能够使用覆盖表面上显示的局部对象来控制获取与监控场景中包含对象的区域相对应的更高分辨率视频。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Framework for Intelligent Video Surveillance
This paper presents a framework for intelligent video surveillance. Robust distortion correction and rendering algorithms permit the system to support a wide range of video stream sources, including 360-degree panoramic video systems, and to facilitate the substitution of video stream sources, leading to increased scalability. Adaptive object detection, classification and tracking algorithms are employed in a progressive training configuration that allows the system to learn from previous mistakes and to improve performance with increased use. Multiple video stream sources can be combined with arbitrarily shaped overlay surfaces designed to overlay spatially resolved and localized detected and tracked objects on global / local maps such as Global Positioning System (GPS)-enabled maps of the monitored scene for vastly improved situational awareness. Another unique feature of the system is the incorporation of bi-directional communication between the overlay surfaces and the rest of the system via the control unit that enables the use of the localized objects displayed on the overlay surfaces to control the acquisition of higher resolution video corresponding to the region containing the objects in the monitored scene.
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