In this paper, a method by applying deep learning method onto the point clouds data for semantic segmentation is proposed. Three convolutional neural networks, PointNet, PointNet++, and DGCNN, are replicated, designed, and analyzed. In order to avoid problems introduced by some other methods due to the preprocessing step, here, PointNet, PointNet++, and DGCNN are directly used onto the 3D point cloud. Experiments verified the effect of these neural networks on point clouds for semantic segmentation. Methods based on PointNet and PointNet++ show good results, while DGCNN-based reached state-of-the-art performance.
Deep Learning on 3D Point Cloud for Semantic Segmentation
Smart Innovation, Systems and Technologies
Advances in Smart Vehicular Technology, Transportation, Communication and Applications ; Chapter : 27 ; 275-282
2021-11-30
8 pages
Article/Chapter (Book)
Electronic Resource
English
Deep Learning on 3D Point Cloud for Semantic Segmentation
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