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首页> 外文会议>Conference on Real-Time Image Processing; 20080128-29; San Jose,CA(US) >Real-time road traffic classification using mobile video cameras
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Real-time road traffic classification using mobile video cameras

机译：使用移动摄像机进行实时道路交通分类

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摘要

On board video analysis has attracted a lot of interest over the two last decades with as main goal to improve safety by detecting obstacles or assisting the driver. Our study aims at providing a real-time understanding of the urban road traffic. Considering a video camera fixed on the front of a public bus, we propose a cost-effective approach to estimate the speed of the vehicles on the adjacent lanes when the bus operates on a dedicated lane. We work on 1-D segments drawn in the image space, aligned with the road lanes. The relative speed of the vehicles is computed by detecting and tracking features along each of these segments. The absolute speed can be estimated from the relative speed if the camera speed is known, e.g. thanks to an odometer and/or GPS. Using pre-defined speed thresholds, the traffic can be classified into different categories such as 'fluid', 'congestion' etc. The solution offers both good performances and low computing complexity and is compatible with cheap video cameras, which allows its adoption by city traffic management authorities.
机译：在过去的二十年中，车载视频分析吸引了很多兴趣，其主要目标是通过发现障碍物或协助驾驶员来提高安全性。我们的研究旨在提供对城市道路交通的实时了解。考虑到安装在公共巴士前部的摄像机，我们提出了一种经济高效的方法来估算公交车在专用车道上行驶时相邻车道上的车辆速度。我们处理在图像空间中绘制的与道路车道对齐的一维线段。车辆的相对速度是通过检测和跟踪这些分段中每个分段的特征来计算的。如果已知相机速度，例如可以从相对速度估计绝对速度。多亏了里程表和/或GPS。使用预定义的速度阈值，可以将流量分为“流体”，“拥塞”等不同类别。该解决方案既具有良好的性能，又具有较低的计算复杂度，并且与廉价的摄像机兼容，因此可以被城市采用交通管理部门。

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