Technology of Graphic & Image
|
1256-1260

Airborne LiDAR point clouds classification algorithm for urban classification using neural network

Shi Xiaosong
Cheng Yinglei
Zhao Zhongyang
College of Information & Navigation, Air Force Engineering University, Xi'an 710077, China

Abstract

In order to apply neural network to urban LiDAR point clouds data classification, and to decrease large computation and long time consuming in the training process of large-scale point clouds data, this paper improved the original PointNet neural network by adding neighborhood characteristics of point clouds, and proposed a new classification algorithm for point clouds. This algorithm compressed the original point clouds data volume through grid clustering and resampling, and then it extracted multi-scale neighborhood point clouds data and classified urban point clouds by using improved PointNet. This paper verified the classification algorithm with data from different regions. The results show that the algorithm has good classification effect, high classification accuracy and less calculation, and can realize effective classification of airborne LiDAR data in urban areas.

Foundation Support

国家自然科学基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.10.0783
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Technology of Graphic & Image
Pages: 1256-1260
Serial Number: 1001-3695(2020)04-064-1256-05

Publish History

[2020-04-05] Printed Article

Cite This Article

释小松, 程英蕾, 赵中阳. 利用神经网络的城区机载激光雷达点云分类算法 [J]. 计算机应用研究, 2020, 37 (4): 1256-1260. (Shi Xiaosong, Cheng Yinglei, Zhao Zhongyang. Airborne LiDAR point clouds classification algorithm for urban classification using neural network [J]. Application Research of Computers, 2020, 37 (4): 1256-1260. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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