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Video road vehicle detection and tracking based on OpenCV

机译:基于OpenCV的视频道路车辆检测与跟踪

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摘要

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using camshift tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.
机译:视频监控广泛用于安全监控,军事导航,智能交通等。其主要研究领域是模式识别,计算机视觉和人工智能。 本文使用OpenCV来检测和跟踪车辆,并通过在静止背景上建立自适应模型来检测车辆。 与传统车辆检测相比,它不仅具有低价格,安装和维护方便,监控范围广泛的优点,而且也可在路上使用。 使用CAMSHIFT跟踪算法的场景图像的智能分析和处理可以收集各种交通流量参数(包括一段时间内的车辆数量)和同时车辆的特定位置,以便解决车辆 抵消。 它在运行中可靠,具有很高的实用价值。

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