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Hough-based recognition of complex 3-D road scenes

机译:基于Hough的复杂3D道路场景识别

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Abstract: In this paper, we address the problem of the object recognition in a complex 3-D scene by detecting the 2-D object projection on the image-plane for an autonomous vehicle driving; in particular, the problems of road detection and obstacle avoidance in natural road scenes are investigated. A new implementation of the Hough Transform (HT), called Labeled Hough Transform (LHT), to extract and group symbolic features is here presented; the novelty of this method, in respect to the traditional approach, consists in the capability of splitting a maximum in the parameter space into noncontiguous segments, while performing voting. Results are presented on a road image containing obstacles which show the efficiency, good quality, and time performances of the algorithm. !10
机译:摘要:本文通过检测自动驾驶车辆在图像平面上的二维物体投影,解决了复杂3-D场景中物体识别的问题。特别地,研究了自然道路场景中的道路检测和避障问题。本文介绍了霍夫变换(HT)的一种新实现,称为标记霍夫变换(LHT),用于提取和分组符号特征。与传统方法相比,此方法的新颖性在于能够在执行投票的同时将参数空间中的最大值拆分为不连续的段。结果显示在包含障碍物的道路图像上,这些障碍物显示了算法的效率,良好的质量和时间性能。 !10

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