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Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

Yueqian Shen1,2, Roderik Lindenbergh3, Jinhu Wang4,5

  • 1School of Earth Science and Engineering, Hohai University, No. 1, Xikang Road, Nanjing 210098, China. syq19881012@126.com.

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Summary
This summary is machine-generated.

This study introduces a novel point cloud change detection method using baselines, eliminating the need for registration. This approach accurately identifies structural damage after seismic events by comparing connected feature points between scans.

Keywords:
baselineschange detectionmasonry buildingsstructural analysisterrestrial laser scanning

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Area of Science:

  • Geomatics Engineering
  • Structural Health Monitoring
  • Geospatial Data Analysis

Background:

  • Change detection in point clouds typically requires registration, a process prone to errors and demanding stable features.
  • Existing methods for analyzing structural changes from 3D scans face limitations due to registration inaccuracies.
  • A need exists for a registration-free method to reliably detect subtle changes in scanned environments.

Purpose of the Study:

  • To develop and validate a novel change detection technique for point clouds that bypasses the traditional registration step.
  • To assess the efficacy of a baseline-based approach for identifying structural deformations, specifically after seismic events.
  • To compare the proposed method's performance against conventional cloud-to-cloud analysis for structural integrity assessment.

Main Methods:

  • A registration-free change detection method is proposed, utilizing 'baselines' that connect feature points within a single scan.
  • Baselines connecting corresponding feature points (targets or virtual points) across two scans are compared to detect changes.
  • The method was applied to point cloud data of a masonry laboratory building before and after seismic testing, using automatically extracted brick centers as virtual points.

Main Results:

  • The baseline analysis successfully detected structural damages in the masonry laboratory building, with deformations measured in centimeters.
  • The proposed method demonstrated its potential for accurate structural analysis by identifying changes without relying on registration.
  • Comparison with traditional cloud-to-cloud change detection highlighted the advantages of the baseline-based approach.

Conclusions:

  • The developed baseline-based method offers a robust and accurate alternative for detecting changes in point clouds, particularly for structural monitoring.
  • This registration-free technique mitigates errors associated with alignment and expands the applicability of 3D scan data analysis.
  • The method shows significant promise for assessing structural health and damage in civil engineering applications.