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Feature Consistent Point Cloud Registration in Building Information Modeling.

Hengyu Jiang1, Pongsak Lasang2, Georges Nader2

  • 1School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210000, China.

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Summary
This summary is machine-generated.

This study introduces PyramidFeature (PMD) for robust point cloud registration in Building Information Modeling (BIM). PMD enhances feature generalization and accuracy, especially in diverse environments.

Keywords:
building information modelingfeature consistentpoint cloud registration

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Area of Science:

  • Computer Vision
  • Geometric Computing
  • 3D Data Processing

Background:

  • Point cloud registration is crucial for Building Information Modeling (BIM) applications like measuring and simulation.
  • Existing methods struggle with generalization due to varying sampling environments and normal ambiguity at object boundaries.
  • Current approaches often prioritize spatial transformation accuracy over feature matching, limiting performance.

Purpose of the Study:

  • To develop a more robust and generalizable point cloud feature extraction method for BIM.
  • To address the challenges of normal ambiguity and improve accuracy in point cloud registration.
  • To enhance feature matching capabilities alongside spatial transformation accuracy.

Main Methods:

  • Proposed a boundary-encouraging local frame reference called PyramidFeature (PMD).
  • PMD integrates point-level, line-level, and mesh-level information for feature extraction.
  • Introduced a hybrid feature extraction supervision method to improve consistency.

Main Results:

  • The proposed PyramidNet (PMDNet) demonstrated superior performance in point cloud registration.
  • PMDNet achieved high scalability and accuracy, even with significantly different training and testing datasets (ModelNet40 and BIM).
  • The method effectively overcomes normal ambiguity at boundaries, leading to more accurate transformations.

Conclusions:

  • PyramidNet (PMDNet) offers a significant advancement in point cloud registration for BIM.
  • The PMD feature extraction method enhances generalization and robustness in diverse environments.
  • This approach improves the reliability of 3D data processing in BIM applications.