An automatic extrinsic parameter calibration method for camera-on-vehicle on structured road

Meng Wu, X. An
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引用次数: 7

Abstract

This paper proposes a novel self-calibration method for getting the extrinsic parameters of the camera on the autonomous vehicle. Basing on the model of the highway and the extrinsic parameters of the camera, the lane marking can be described parametrically in the vehicle coordinate system. The position and headings of the vehicle can be measured by itself in real time. Thus the Extended Kalman Filter can be applied to the kinematical model of the vehicle. By this means, it is possible to refine the original rough extrinsic parameters of the camera with an iterative way. Experiment results show that this method has a good performance in the structural scenery on highway.
结构化道路上车载摄像机外部参数自动标定方法
提出了一种获取自动驾驶汽车摄像机外部参数的自标定方法。基于公路模型和摄像机的外部参数,可以在车辆坐标系中对车道标线进行参数化描述。车辆的位置和航向可以自行实时测量。因此,扩展卡尔曼滤波可以应用于车辆的运动学模型。通过这种方法,可以用迭代的方式对相机的原始粗糙外部参数进行细化。实验结果表明,该方法在高速公路结构景观中具有较好的效果。
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