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Stereovision-Based Sensor for Intersection Assistance

机译:基于立体视觉的交叉口辅助传感器

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摘要

The intersection scenario imposes radical changes in the physical setup and in the processing algorithms of a stereo sensor. Due to the need for a wider field of view, which comes with distortions and reduced depth accuracy, increased accuracy in calibration and dense stereo reconstruction is required. The stereo matching process has to be performed on rectified images, by a dedicated stereo board, to free processor time for the high-level algorithms. In order to cope with the complex nature of the intersection, the proposed solution perceives the environment in two modes: a structured approach, for the scenarios where the road geometry is estimated from lane delimiters, and an unstructured approach, where the road geometry is estimated from elevation maps. The structured mode provides the parameters of the lane, and the position, size, speed and class of the static and dynamic objects, while the unstructured mode provides an occupancy grid having the cells labeled as free space, obstacle areas, curbs and isles.
机译:相交方案在物理设置和立体传感器的处理算法中施加了根本性的变化。由于需要更宽的视野,因此会带来失真和降低的深度精度,因此需要提高校准精度和密集的立体声重建。立体声匹配过程必须由专用的立体声板在整流后的图像上执行,以腾出处理器时间用于高级算法。为了应对交叉路口的复杂性,建议的解决方案以两种模式感知环境:针对从车道定界符估计道路几何形状的方案,使用结构化方法;对于估计道路几何形状的方法,采用非结构化方法从高程图。结构化模式提供车道的参数,以及静态和动态对象的位置,大小,速度和类别,而非结构化模式则提供一个占用网格,其中的单元格标记为自由空间,障碍区域,路缘和小岛。

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