Lidar Image Classification based on Convolutional Neural Networks

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International Journal of Advanced Network, Monitoring and Controls

Xi'an Technological University

Subject: Computer Science, Software Engineering

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eISSN: 2470-8038

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VOLUME 2 , ISSUE 3 (September 2017) > List of articles

Lidar Image Classification based on Convolutional Neural Networks

Yang Wenhui * / Yu Fan

Keywords : Point Cloud, CNN, Gray Image, Lidar,

Citation Information : International Journal of Advanced Network, Monitoring and Controls. Volume 2, Issue 3, Pages 158-162, DOI: https://doi.org/10.1109/iccnea.2017.37

License : (CC BY-NC-ND 4.0)

Published Online: 09-April-2018

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This paper presents a new method of recognition of lidar cloud point images based on convolutional neural network. This experiment uses 3D CAD ModelNet, and generates 3D point cloud data by simulating the scanning process of lidar. The data is divided into cells, and the distance is represented by gray values. Finally, the data is stored as grayscale images. Changing the number of cells dividing point cloud results in different experimental results. Experiments show that the proposed method has higher accuracy when dividing the cloud with 27x35 cells. Comparison of point cloud cell image method with VoxNet method, experimental results show that the classification method based on gray image and convolutional neural network has more advantages than the most advanced point cloud recognition network Voxnet.

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