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Collision Sensing by Stereo Vision and Radar Sensor Fusion

机译:立体视觉和雷达传感器融合的碰撞感应

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摘要

To take advantage of both stereo cameras and radar, this paper proposes a fusion approach to accurately estimate the location, size, pose, and motion information of a threat vehicle with respect to a host one from observations that are obtained by both sensors. To do that, we first fit the contour of a threat vehicle from stereo depth information and find the closest point on the contour from the vision sensor. Then, the fused closest point is obtained by fusing radar observations and the vision closest point. Next, by translating the fitted contour to the fused closest point, the fused contour is obtained. Finally, the fused contour is tracked by using rigid body constraints to estimate the location, size, pose, and motion of the threat vehicle. Experimental results from both synthetic data and real-world road test data demonstrate the success of the proposed algorithm.
机译:为了同时利用立体摄像机和雷达,本文提出了一种融合方法,可以根据两个传感器获得的观测结果准确地估计威胁车辆相对于宿主车辆的位置,大小,姿态和运动信息。为此,我们首先根据立体深度信息拟合威胁车辆的轮廓,然后从视觉传感器找到轮廓上的最近点。然后,通过融合雷达观测值和视觉最近点获得融合的最近点。接下来,通过将拟合轮廓平移到融合最近点,就可以得到融合轮廓。最后,通过使用刚体约束来跟踪融合轮廓,以估计威胁车辆的位置,大小,姿势和运动。综合数据和实际道路测试数据的实验结果证明了该算法的成功。

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