Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Geometrically-driven underground camera modeling and calibration with coplanarity constraints for Boom-type roadheader

Yang, W, Zhang, X, Ma, H and Zhang, G (2020) Geometrically-driven underground camera modeling and calibration with coplanarity constraints for Boom-type roadheader. IEEE Transactions on Industrial Electronics. ISSN 0278-0046

[img]
Preview
Text
manuscript_20200520.pdf - Accepted Version

Download (2MB) | Preview

Abstract

The conventional calibration methods based on perspective camera model are not suitable for underground camera with two-layer glasses, which is specially designed for explosion-proof and dust removal in coal mine. The underground camera modeling and calibration algorithms are urgently needed to improve the precision and reliability of underground visual measurement system. This paper presents a novel geometrically-driven underground camera calibration algorithm for Boom-type roadheader. The underground camera model is established under coplanarity constraints, considering explicitly the impact of refraction triggered by the two-layer glasses and deriving the geometrical relationship of equivalent collinearity equations. On this basis, we perform parameters calibration based on a geometrically-driven calibration model, which is a 2D-2D correspondences between the image points and object coordinates of the plannar target. A hybrid LM-PSO algorithm is further proposed in terms of the dynamic combination of the Levenberg-Marqurdt (LM) and Particle Swarm Optimization (PSO), which optimize the underground camera calibration results by minimizing the error of the nonlinear underground camera model. The experiment results demonstrate that the pose errors caused by the two-layer glass refraction are well corrected by the proposed method. The accuracy of the cutting-head pose estimation has increased by 55.73%, meeting the requirements of underground excavations.

Item Type: Article
Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: 08 Information and Computing Sciences, 09 Engineering
Subjects: T Technology > T Technology (General)
T Technology > TN Mining engineering. Metallurgy
T Technology > TR Photography
Divisions: Engineering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date Deposited: 09 Oct 2020 10:39
Last Modified: 09 Oct 2020 10:39
DOI or Identification number: 10.1109/tie.2020.3018072
URI: https://researchonline.ljmu.ac.uk/id/eprint/13559

Actions (login required)

View Item View Item