Self-calibrated dense 3D sensor using multiple cross line-lasers based on light sectioning method and visual odometry

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

1 Citation (Scopus)

Abstract

Among various 3D capturing systems, since the system with line lasers based on the light sectioning method is simple and accurate, it has widely attracted many developers and used for many purposes. In addition, there is no need to synchronize the camera and the laser and also the configuration of the camera and the lasers is flexible, and thus, the system can be used for extreme conditions, such as underwater. There are two open problems for the system. The first problem is a low density of the 3D shape obtained from a single image, i.e., just several curves. The second problem is the accuracy of line detection in the wild. In this paper, we propose a self-calibration method using visual odometry (VO) to bundle a large number of frames to increase the density to solve the first problem. We also propose a robust line detection algorithm using CNN to solve the second problem. Comparative experiments prove the effectiveness of our proposed method. In addition, the system was tested in the extreme condition for demonstration.

Original languageEnglish
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-100
Number of pages7
ISBN (Electronic)9781665417143
DOIs
Publication statusPublished - 2021
Event2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 - Prague, Czech Republic
Duration: Sep 27 2021Oct 1 2021

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Country/TerritoryCzech Republic
CityPrague
Period9/27/2110/1/21

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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