Self-calibration of multiple-line-lasers based on coplanarity and Epipolar constraints for wide area shape scan using moving camera

Genki Nagamatsu, Takaki Ikeda, Takafumi Iwaguchi, Diego Thomas, Jun Takamatsu, Hiroshi Kawasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

High-precision three-dimensional scanning systems have been intensively researched and developed. Recently, for acquisition of large scale scene with high density, simultaneous localisation and mapping (SLAM) technique is preferred because of its simplicity; a single sensor that is moved around freely during 3D scanning. However, to integrate multiple scans, captured data as well as position of each sensor must be highly accurate, making these systems difficult to use in environments not accessible by humans, such as underwater, internal body, or outer space. In this paper, we propose a new, flexible system with multiple line lasers that reconstructs dense and accurate 3D scenes. The advantages of our proposed system are (1) no need of synchronization nor precalibration between lasers and a camera, and (2) the system can reconstruct 3D scenes in extreme conditions, such as underwater. We propose a new self-calibration method leveraging coplanarity and Epipolar constraints is proposed. We also propose a new bundle adjustment (BA) technique that is tailored to the system for a dense integration of multiple line laser scans. Experimental evaluation in both air and underwater environments confirms the advantages of the proposed method.

Original languageEnglish
Title of host publication2022 26th International Conference on Pattern Recognition, ICPR 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3959-3965
Number of pages7
ISBN (Electronic)9781665490627
DOIs
Publication statusPublished - 2022
Event26th International Conference on Pattern Recognition, ICPR 2022 - Montreal, Canada
Duration: Aug 21 2022Aug 25 2022

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2022-August
ISSN (Print)1051-4651

Conference

Conference26th International Conference on Pattern Recognition, ICPR 2022
Country/TerritoryCanada
CityMontreal
Period8/21/228/25/22

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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