This paper covers the problem of road surface reconstruction by stereo vision with cameras placed behind the windshield of a moving vehicle. An algorithm was developed that employs a plane-sweep approach and uses semi-global matching for optimization. Different similarity measures were evaluated for the task of matching pixels, namely mutual information, background subtraction by bilateral filtering, and Census. The chosen sweeping direction is the plane normal of the mean road surface. Since the cameras’ position in relation to the base plane is continuously changing due to the suspension of the vehicle, the search for the base plane was integrated into the stereo algorithm. Experiments were conducted for different types of pavement and different lighting conditions. Results are presented for the target application of road surface reconstruction, and they show high correspondence to laser scan reference measurements. The method handles motion blur well, and elevation maps are reconstructed on a millimeter-scale, while images are captured at driving speed.

本文介绍了通过在移动车辆的挡风玻璃后面放置摄像头通过立体视觉重建路面的问题。开发了一种采用平面扫描方法并使用半全局匹配进行优化的算法。对于匹配像素的任务，评估了不同的相似性度量，即互信息，通过双边滤波进行的背景扣除和人口普查。选择的扫掠方向为平均路面的法线方向。由于车辆的悬架，相机相对于基准面的位置不断变化，因此对基准面的搜索已集成到立体算法中。针对不同类型的路面和不同的照明条件进行了实验。提出了针对路面重建目标应用的结果，它们与激光扫描参考测量值显示出高度对应性。该方法能够很好地处理运动模糊，并以毫米级重建高程图，同时以行驶速度捕获图像。