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Road marking recognition for map generation using sparse tensor voting

机译:使用稀疏张量投票生成地图的道路标记识别

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A recognition method of road markings for map generation is presented. For accurate position estimation and classification, two voting schemes are proposed and combined. The first is multi-frame sparse tensor voting for geometric feature extraction, and the second is contour localization using the resulting tensor field. Classification is based on the similarity between the aligned contour and the tensor field. The experimental results show that the proposed method outperforms conventional matching-based approaches.
机译:提出了一种用于地图生成的道路标记识别方法。为了进行准确的位置估计和分类,提出并组合了两种投票方案。第一个是用于几何特征提取的多帧稀疏张量投票,第二个是使用所得张量场的轮廓定位。分类基于对齐的轮廓和张量场之间的相似性。实验结果表明,该方法优于传统的基于匹配的方法。

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