3D vehicle sensor based on monocular vision
3D vehicle sensor based on monocular vision
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DOI：
10.1109/itsc.2005.1520204
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发表时间：
2005-10
期刊：
影响因子：
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通讯作者：
D. Ponsa;Antonio M. López;F. Lumbreras;J. Serrat;Thorsten Graf
中科院分区：
文献类型：
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作者：
D. Ponsa;Antonio M. López;F. Lumbreras;J. Serrat;Thorsten Graf
确定其他车辆在道路上的位置是帮助驾驶员辅助系统提高驾驶员安全性的关键信息。因此，本文提出了一种利用单色摄像机检测前方车辆并估计其三维位置的方法。与使用对称性、阴影搜索等预定义的高级图像特征不同，我们的车辆检测建议基于一个学习过程，该过程从训练集中确定哪些特征是区分车辆和非车辆的最佳特征。要用一台摄像机计算3D信息，关键的一点是知道地平线投影到图像上的位置。但是，该位置可能在每一帧中都会发生变化，因此很难确定。在本文中，我们研究了感知地平线和车辆实际宽度之间的耦合，以减少未知地平线对车辆估计的3D位置的不确定性。
Determining the position of other vehicles on the road is a key information to help driver assistance systems to increase driver's safety. Accordingly, the work presented in this paper addresses the problem of detecting the vehicles in front of our own one and estimating their 3D position by using a single monochrome camera. Rather than using predefined high level image features as symmetry, shadow search, etc., our proposal for the vehicle detection is based on a learning process that determines, from a training set, which are the best features to distinguish vehicles from non-vehicles. To compute 3D information with a single camera a key point consists of knowing the position where the horizon projects onto the image. However, this position can change in every frame and is difficult to determine. In this paper we study the coupling between the perceived horizon and the actual width of vehicles in order to reduce the uncertainty in their estimated 3D position derived from an unknown horizon.