{"id":{"repo_id":"calgary","oai_identifier":"oai:ucalgary.scholaris.ca:1880/112077"},"canonical_url":"https://search.dev.ndltd.org/etd/calgary/oai:ucalgary.scholaris.ca:1880/112077","repository":{"repo_id":"calgary","name":"University of Calgary","base_url":"https://ucalgary.scholaris.ca/server/oai/request"},"display":{"title":"Wide-angle Lens Camera Calibration using Automatic Target Recognition","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Jarron, David Mackenzie"],"institution":"Schulich School of Engineering","degree_name":"Master of Science (MSc)","degree_level":null,"degree_discipline":"Engineering – Geomatics","degree_department":null,"school":null,"contributors":[],"advisors":["Lichti, Derek D.","Shahbazi, Mozhdeh M."],"committee_chairs":[],"committee_members":["O'Keefe, Kyle P. G.","Detchev, Ivan D."],"year":2020,"date_issued":"2020-05-15","date_published":"2020-05-15","updated_at":"2026-07-24T01:30:25Z","subjects":["Camera Calibration","Mobile Mapping Systems"],"languages":["eng"],"rights":["University of Calgary graduate students retain copyright ownership and moral rights for their thesis. 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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."]},{"key":"dc:title","label":"Title","values":["Wide-angle Lens Camera Calibration using Automatic Target Recognition"]}]}],"canonical_facts":{"dc:contributor.advisor":["Lichti, Derek D.","Shahbazi, Mozhdeh M."],"dc:contributor.committeemember":["O'Keefe, Kyle P. 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