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Template matching for radar-based orientation and position estimation in automotive scenarios

机译:用于汽车场景中基于雷达的方向和位置估计的模板匹配

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Future high-resolution radars enable new functionalities in advanced driver assistance systems, such as estimation of contour, position, and orientation of vehicles on the road. However, straightforward approaches like that of Oriented Bounding Box generally fail in challenging automotive scenarios, when only one side of the vehicle is visible to the radar. In this paper, an estimation approach based on Generalized Hough Transform matching is presented and examined for its use in such automotive scenarios. An optimization method is discussed and finally, the algorithm is compared against a classic approach.
机译:未来的高分辨率雷达将在高级驾驶员辅助系统中实现新功能,例如估算道路上车辆的轮廓,位置和方向。但是,当雷达只能看到车辆的一侧时,像定向边界盒这样的简单方法通常在具有挑战性的汽车场景中会失败。在本文中,提出了一种基于广义霍夫变换匹配的估计方法,并研究了其在此类汽车场景中的使用。讨论了一种优化方法,最后将该算法与经典方法进行了比较。

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