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Schulich School of Engineering

Wide-angle Lens Camera Calibration using Automatic Target Recognition

Abstract

dc:description.abstract

The focus of this thesis is the calibration and integration of the Ladybug5 multi-camera system into a Mobile Mapping System. To calibrate this system an efficient and accurate automatic target recognition methodology that could work with a multi-camera system was needed. This automatic target recognition methodology was developed and works by projecting the known coordinates of the surveyed calibration targets into the camera frame through a series of simulated or measured orientations and matching to signalized targets already detected in the image to a very high degree of accuracy. Through calibration of this system and rigorous modelling of its intrinsic properties, it became apparent that there was ambiguity in the research field about the most precise projection model to use for wide angle lens cameras and camera systems. A series of camera calibrations were carried out on two wide angle camera systems. Both camera systems exhibit properties that make them difficult to classify as either a central perspective camera or as a fisheye camera. Calibrations were performed on both camera systems using both central perspective and fisheye projection models. The calibrations that utilized a fisheye projection model estimated calibration parameters that more closely fit the observations. Finally, the calibration of the Ladybug5 as a multi-camera system, utilizing ROP stability constraints was performed to rectify issues relating to issues with the panoramic image generation of the Ladybug5. These panoramic images are important for point cloud coloration, and other aspects of multi-camera system integration with mobile mapping systems. It was determined that the calibration of the Ladybug5 using relative orientation stability constraints allowed for the generation of more seamless panoramic images, allowing the camera to better integrate with mobile mapping systems.

Degree

thesis:*
Name thesis:degree_name
Master of Science (MSc)
Discipline thesis:degree_discipline
Engineering – Geomatics
Grantor dc:publisher.institution
Schulich School of Engineering
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Jarron, David Mackenzie
Advisors dc:contributor.advisor
  • Lichti, Derek D.
  • Shahbazi, Mozhdeh M.
Committee members dc:contributor.committeemember
  • O'Keefe, Kyle P. G.
  • Detchev, Ivan D.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:ucalgary.scholaris.ca:1880/112077

Chain of custody

source
Harvested from
University of Calgary
Base URL
ucalgary.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Jarron, David Mackenzie. Wide-angle Lens Camera Calibration using Automatic Target Recognition. Schulich School of Engineering, 2020. http://hdl.handle.net/1880/112077