基于视频的实时交通监控系统中的影子处理器

M. Kilger
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引用次数: 214

摘要

提出了一种基于视频的交通监控系统。该系统的目标是建立交通场景的高级描述,包括车辆的位置,速度和类别。提出了运动目标的检测、车辆与阴影的分离、跟踪和分类算法。在阳光充足的条件下,如果没有将阴影与车辆分开,则很难对车辆进行分类。这种分类方法在低成本硬件上实时运行。影子可以从车辆中分离出来,并且可以有效地利用关于影子形状的知识。阴影分析算法本身使用了关于场景几何(观察道路的方向)和全局数据(日期和时间)的高级知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A shadow handler in a video-based real-time traffic monitoring system
A video-based system for traffic monitoring is presented. The objective of the system is to set up a high-level description of the traffic scene comprising the position, speed and class of the vehicles. Algorithms for detecting moving objects, separating the vehicles from their shadows, tracking and classification are presented. The classification of vehicles under sunny conditions is very difficult, if the shadow isn't separated from the vehicles. This approach for classification runs in real-time on low-cost hardware. the shadow can be separated from the vehicle and the knowledge about the shape of the shadow can be efficiently used. The shadow analysis algorithm itself uses high-level knowledge about the geometry of the scene (heading of the observed road) and about global data (date and time).<>
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