A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
As a key step in 3D scene analysis, point cloud classification has gained a great deal of concerns in the past few years. Due to the uneven density, noise and data missing in point cloud, how to automatically classify the point cloud with a high precision is a very challenging task. The point cloud classification process typically includes the extraction of neighborhood based statistical information and machine learning algorithms. However, the robustness of neighborhood is limited to thedoi:10.5194/isprs-archives-xlii-2-w7-219-2017 fatcat:2znoklan6bejhe56aemswhgazu