An effective method to segment vehicles and roads is proposed for autonomous vehicles using low-channel 3D lidar. The distance-view transformation is newly proposed to overcome the low density of top-view data of lidar. In addition, a dilated convolution structure is proposed to expand the receptive field of a convolutional neural network. The proposed network improves the accuracy of segmentation. The experimental results are presented to verify the usefulness of the proposed method.


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    Title :

    Segmentation of Vehicles and Roads by a Low-Channel Lidar


    Contributors:


    Publication date :

    2019-11-01


    Size :

    2592623 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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