Point cloud labeling using 3D Convolutional Neural Network

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 prev...

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Bibliographic Details
Published in2016 23rd International Conference on Pattern Recognition (ICPR) pp. 2670 - 2675
Main Authors Jing Huang, Suya You
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Labeling
Neural networks
Testing
Three-dimensional displays
Training
Training data
Two dimensional displays
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Summary: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.
DOI:10.1109/ICPR.2016.7900038