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Detection of parked vehicles from a radar based occupancy grid

机译:从基于雷达的占用栅格中检测停放的车辆

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摘要

For autonomous parking applications to become possible, knowledge about the parking environment is required. Therefore, a real-time algorithm for detecting parked vehicles from radar data is presented. These data are first accumulated in an occupancy grid from which objects are detected by applying techniques borrowed from the computer vision field. Two random forest classifiers are trained to recognize two categories of objects: parallel-parked vehicles and cross-parked vehicles. Performances of the classifiers are evaluated as well as the capacity of the complete system to detect parked vehicles in real world scenarios.
机译:为了使自动停车应用成为可能,需要有关停车环境的知识。因此,提出了一种从雷达数据中检测停放车辆的实时算法。这些数据首先存储在一个占用网格中,通过应用从计算机视觉领域借来的技术从中检测对象。训练了两个随机森林分类器以识别两类物体:平行停放的车辆和交叉停放的车辆。评估分类器的性能以及整个系统在现实情况下检测停放车辆的能力。

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