Point Cloud Labeling using 3D Convolutional Neural Network

Jing Huang, Suya You

Abstract:

In this paper, we tackle the labeling problem for 3D point clouds. We introduce a 3D point cloud labeling scheme
based on 3D Convolutional Neural Network. Our approach minimizes the prior knowledge of the labeling problem and does
not require a segmentation step or hand-crafted features as most previous approaches did. Particularly, we present solutions for large data handling during the training and testing process. Experiments performed on the urban point cloud dataset containing 7 categories of objects show the robustness of our approach.