Academic Journal of Computing & Information Science, 2022, 5(12); doi: 10.25236/AJCIS.2022.051209.
Yunming Liu1, Yuanxiao Liu2
1School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
2The No.2 Middle School of Qingzhou, Weifang, Shandong, 262500, China
Nowadays, with the development of 3D filtering information processing by data algorithms, people have deeply studied 3D data processing. A series of issues were found in the research process. Moreover, the current research on point cloud data in the use of lidar is not comprehensive. Its research focuses on noise reduction and data block segmentation of point cloud-filtered data. Based on the above background, this paper analyzes the bilateral characteristics of point cloud filtering data in detail. It improves the adaptive clustering network to cluster the sample center points of the point cloud filtering data, effectively improving its readability and processing characteristics.
Point cloud filtering; Self-adaptive algorithm; Euclidean clustering; Convolutional neural network
Yunming Liu, Yuanxiao Liu. Research on Point Cloud Filtering Data Processing Method Based on Self-adaptive Euclidean Clustering Network. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 12: 60-66. https://doi.org/10.25236/AJCIS.2022.051209.
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