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An ICP-Based Point Clouds Registration Method for Indoor Environment Modeling

  • 2020
  • OriginalPaper
  • Chapter
Published in:
Authors
Su Sun
Wei Song
Yifei Tian
Simon Fong
Published in
Advanced Multimedia and Ubiquitous Engineering
Publisher
Springer Singapore

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Abstract

LiDAR has been widely used in 3D reconstruction due to its high resolution, wide range and tolerance towards light and weather. To realize accurate and complete environment perception and reconstruction, LiDAR point cloud registration plays a crucial role. This paper utilized an Iterative Closest Point (ICP) algorithm to register the sparse point cloud sensed by LiDAR into a whole indoor environment model. Instead of using a standard ICP algorithm, a point-to-plane ICP is adopted with point cloud selection, point pair matching and rejection. The transformation value between two point cloud data is iteratively calculated and optimized until the defined error metric reaches convergence.

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previous chapter A Hierarchical Attention Headline Generation Model with a Filter
next chapter Particle Color Transforming Method by Mapping Image Texture Arrangement with Weight Value
Title
An ICP-Based Point Clouds Registration Method for Indoor Environment Modeling
Authors
Su Sun
Wei Song
Yifei Tian
Simon Fong
Copyright Year
2020
Publisher
Springer Singapore
Book
Advanced Multimedia and Ubiquitous Engineering

Print ISBN: 978-981-329-243-7

Electronic ISBN: 978-981-329-244-4

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-32-9244-4_48
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