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Pedestrian Detection and Tracking Algorithm Design in Transportation Video Monitoring System

机译:运输视频监控系统中的行人检测与跟踪算法设计

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Recently, the video-based technologies play an important role in monitoring fields, including the detection, identification and tracking of moving object. This paper designs an effective pedestrian detection and tracking algorithm in the traffic environment. Firstly, extract the moving prospect from the background in the video images, using conventional frame difference algorithm. The moving targets extracted include pedestrians, vehicles, the shadow of vehicles and the shaking tree at the side of roads. Then we analyze the geometry features of moving targets. According to the prior knowledge of pedestrian shape, the pedestrians are separated from the moving targets. Finally, on the basis of pedestrian detection and identification, we propose a tracking algorithm based on a combination of particle filter and mean shift. Test results showed that the algorithm have better real-time ability and robustness.
机译:最近,基于视频的技术在监视领域发挥着重要作用,包括检测,识别和移动对象的识别和跟踪。本文在交通环境中设计了一种有效的行人检测和跟踪算法。首先,使用传统的帧差算法从视频图像中的背景中提取从背景中的移动前景。提取的移动目标包括行人,车辆,车辆的影子和道路侧的摇动树。然后我们分析移动目标的几何特征。根据行人形状的先验知识,行人与移动目标分开。最后,在行人检测和识别的基础上,我们提出了一种基于粒子滤波器和平均移位的组合的跟踪算法。测试结果表明,该算法具有更好的实时能力和鲁棒性。

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