Computing Thermal Point Clouds by Fusing RGB-D and Infrared Images: From Dense Object Reconstruction to Environment Mapping

Tanhao Zhang, Luyin Hu, Yuxiang Sun, Lu Li, David Navarro-Alarcon

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Compared with 2D thermal images, visualizing the temperature of objects with their corresponding 3D surfaces provides a more intuitive way to perceive the environment. In this paper, we present an integrated system for large-scale and real-time 3D thermographic reconstruction through fusion of visible, infrared and depth images. The system is composed of an RGB-D and a thermal camera, whose image measurements are aligned with respect to the same coordinate frame. A thermal direct method based on infrared features is proposed and integrated into state-of-art localization algorithms for generating reliable 3D thermal point clouds. The reported experimental results demonstrate that our approach can be used for 3D reconstruction of small and large scale environments based on dual spectrum 3D information.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1707-1714
Number of pages8
ISBN (Electronic)9781665481090
DOIs
Publication statusPublished - Dec 2022
Event2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022 - Jinghong, China
Duration: 5 Dec 20229 Dec 2022

Publication series

Name2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

Conference

Conference2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
Country/TerritoryChina
CityJinghong
Period5/12/229/12/22

ASJC Scopus subject areas

  • Artificial Intelligence
  • Aerospace Engineering
  • Automotive Engineering
  • Control and Optimization
  • Modelling and Simulation

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