智能摄像机的鲁棒交通状态估计

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI:10.1109/AVSS.2012.63

Felix Pletzer, R. Tusch, L. Böszörményi, B. Rinner

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引用次数: 12

摘要

提出了一种基于智能摄像头的高速公路视频交通状态检测新方法。摄像机标定参数由已知的车道标线长度获得。采用鲁棒离群值检测的kade - lucas - tomasi (KLT)光流法估计了平均交通速度。采用稳健统计计数方法估计交通密度。我们的方法已经在嵌入式智能摄像头上实现，并在不同的道路和照明条件下进行了评估。对静止交通的检测率达到95%以上。

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Robust Traffic State Estimation on Smart Cameras

This paper presents a novel method for video-based traffic state detection on motorways performed on smart cameras. Camera calibration parameters are obtained from the known length of lane markings. Mean traffic speed is estimated from Kanade-Lucas-Tomasi (KLT) optical flow method using a robust outlier detection. Traffic density is estimated using a robust statistical counting method. Our method has been implemented on an embedded smart camera and evaluated under different road and illumination conditions. It achieves a detection rate of more than 95% for stationary traffic.

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来源期刊

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance

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