Assessment of Camera Pose Estimation Using Geo-Located Images from Simultaneous Localization and Mapping
Date of Award
Master of Science in Electrical Engineering
Department of Electrical and Computer Engineering
Aaron J. Canciani, PhD
This research proposes a method for enabling low-cost camera localization using geo-located images generated with factorgraph-based Simultaneous Localization And Mapping (SLAM). The SLAM results are paired with panoramic image data to generate geo-located images, which can be used to locate and orient low-cost cameras. This study determines the efficacy of using a spherical camera and LIDAR sensor to enable localization for a wide range of cameras with low size, weight, power, and cost. This includes determining the accuracy of SLAM when geo-referencing images, along with introducing a promising method for extracting range measurements from monocular images of known features.
DTIC Accession Number
Beargie, David W., "Assessment of Camera Pose Estimation Using Geo-Located Images from Simultaneous Localization and Mapping" (2019). Theses and Dissertations. 2245.