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Deep learning based curb detection with Lidar
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作者 WANG Xiaohua LIAO Zhonghe +1 位作者 MA Pin MIAO Zhonghua 《High Technology Letters》 EI CAS 2022年第3期272-279,共8页
Curb detection provides road boundary information and is important to road detection.However,curb detection is challenging due to the problems such as various curb shapes,colour,discontinuity.In this work,a novel lear... Curb detection provides road boundary information and is important to road detection.However,curb detection is challenging due to the problems such as various curb shapes,colour,discontinuity.In this work,a novel learning-based method for curb detection is proposed using Lidar point clouds,considering that Lidars are not sensitive to illumination and are relatively stable to weather conditions.A deep neural network,named EdgeNet,is constructed and trained,which handles point clouds in an end-to-end way.After EdgeNet is properly trained,curb points are then segmented in the neural network output.In order to train,a curb point annotation algorithm is also designed to generate training dataset.The curb detection method works well with different road scenarios including intersections.The experimental results validate the effectiveness and robustness of this curb detection method. 展开更多
关键词 curb detection EdgeNet curb annotation algorithm
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