A model-driven approach for real-time road recognition
A model-driven approach for real-time road recognition
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DOI：
10.1007/pl00013275
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发表时间：
2001-11-01
影响因子：
3.3
通讯作者：
Chausse, F
中科院分区：
文献类型：
--
作者：
Aufrére, R;Chapuis, R;Chausse, F
本文介绍了一种旨在从车载单目单色相机提供的图像开始检测和跟踪道路边缘的方法。 VELAC 项目的框架中也介绍了其在特定硬件上的实现。该方法基于四个模块：（1）通过模型驱动算法检测图像中的道路边缘，该算法使用车道两侧的统计模型来管理道路标记的遮挡或缺陷 - 该模型通过离线训练步骤进行初始化； (2) 车辆在其行驶车道上的定位； (3)跟踪为下一张图像定义新的道路边缘搜索空间； (4)车道号管理，确定车辆行驶的车道。实施该算法是为了在实时环境中验证该方法。在标记和未标记道路图像上获得的结果表明了该方法的鲁棒性和精度。
This article describes a method designed to detect and track road edges starting from images provided by an onboard monocular monochromic camera. Its implementation on specific hardware is also presented in the framework of the VELAC project. The method is based on four modules: (1) detection of the road edges in the image by a model-driven algorithm, which uses a statistical model of the lane sides which manages the occlusions or imperfections of the road marking - this model is initialized by an off-line training step; (2) localization of the vehicle in the lane in which it is travelling; (3) tracking to define a new search space of road edges for the next image; and (4) management of the lane numbers to determine the lane in which the vehicle is travelling. The algorithm is implemented in order to validate the method in a real-time context. Results obtained on marked and unmarked road images show the robustness and precision of the method.