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Automatic detection of discontinuities from 3D point clouds for the stability analysis of jointed rock masses
We describe an strategy for automatic detection of discontinuities in jointed rock masses from a 3D point cloud. The method consists on a sequence of processes for feature extraction and characterization of the discontinuities that use voxelization, robust detection of planes by sequential RANSAC an...
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Main Authors: | , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | We describe an strategy for automatic detection of discontinuities in jointed rock masses from a 3D point cloud. The method consists on a sequence of processes for feature extraction and characterization of the discontinuities that use voxelization, robust detection of planes by sequential RANSAC and clustering. The results obtained by applying this methodology to the 3D point cloud are a set of discontinuity families, characterized by their dips and dip directions, and surface wedges. This geometric information is essential for a later stability analysis of the jointed rock mass. The ultimate aim of our investigation is the automatic extraction of discontinuity families for stability analysis of tunnels excavated in jointed rock masses. |
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DOI: | 10.1109/VSMM.2012.6365985 |