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Related Experiment Video

Updated: May 26, 2026

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
07:58

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

Mobile calibration based on laser metrology and approximation networks.

J Apolinar Muñoz-Rodriguez1

  • 1Centro de Investigaciones en Optica, Loma del Bosque 115, Col. Lomas del campestre, C.P. 37150, Leon, Guanajuato, Mexico. munoza@foton.cio.mx

Sensors (Basel, Switzerland)
|December 14, 2011
PubMed
Summary

This study introduces a mobile calibration technique for 3D vision systems. It enhances accuracy and performance by enabling online re-calibration without external references, improving 3D visualization capabilities.

Keywords:
Bezier networkslaser line projectionmobile calibrationthree-dimensional vision

Related Experiment Videos

Last Updated: May 26, 2026

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
07:58

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

Area of Science:

  • Computer Vision
  • Robotics
  • Metrology

Background:

  • Traditional 3D vision calibration methods often require static setups and reference markers, limiting flexibility and accuracy during dynamic operations.
  • Online re-calibration is crucial for maintaining 3D vision system performance when environmental or setup geometry changes.

Purpose of the Study:

  • To present a novel mobile calibration technique for 3D vision systems that allows for online re-calibration without external references.
  • To improve the accuracy and performance of 3D vision systems through automated parameter computation and visualization.
  • To overcome limitations associated with traditional calibration methods when setup geometry is modified.

Main Methods:

  • Utilizing approximation networks trained on camera position and laser line image processing to compute vision parameters.
  • Implementing online re-calibration based on network-derived data to adjust extrinsic and intrinsic camera parameters.
  • Performing 3D visualization using the developed approximation networks.

Main Results:

  • The proposed mobile calibration technique successfully performs online re-calibration, adapting to modifications in setup geometry.
  • The system demonstrates improved accuracy and performance in 3D vision compared to traditional methods that rely on calibrated references.
  • Processing time for the mobile calibration technique was evaluated and found to be efficient.

Conclusions:

  • The mobile calibration technique offers a robust solution for dynamic 3D vision applications, enhancing system reliability.
  • This method eliminates the need for external references, simplifying the calibration process and reducing potential error sources.
  • The developed approach contributes significantly to the field of online re-calibration for 3D vision systems.