Browsing by Author "Jarron, David"
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- ItemOpen AccessGeometric modelling and calibration of a spherical camera imaging system(2020-04-16) Lichti, Derek D.; Jarron, David; Tredoux, Wynand; Shahbazi, Mozhdeh M.; Radovanovic, RobertThe Ladybug5 is an integrated, multi-camera system that features a near-spherical field of view. It is commonly deployed on mobile mapping systems to collect imagery for 3D reality capture. This paper describes an approach for the geometric modelling and self-calibration of this system. The collinearity equations of the pinhole camera model are augmented with five radial lens distortion terms to correct the severe barrel distortion. Weighted relative orientation stability constraints are added to the self-calibrating bundle adjustment solution to enforce the angular and positional stability between the Ladybug5’s six cameras. Results are presented from two calibration data-sets and an independent data-set for accuracy assessment. It is demonstrated that centimetre-level 3D reconstruction accuracy can be achieved with the proposed approach. Moreover, the effectiveness of the lens distortion modelling is demonstrated. Image-space precision and object-space accuracy are improved by 92% and 93%, respectively, relative to a two-term model. The high correlations between lens distortion coefficients were not found to be detrimental to the solution. The mechanical stability of the system was assessed by comparing calibrations taken before and after ten months of routine camera system use. The results suggest sub-pixel interior orientation stability and millimetre-level relative orientation stability. Analyses of accuracy and parameter correlation demonstrate that a slightly-relaxed weighting strategy is preferred to tightly-enforced relative orientation stability constraints.
- ItemOpen AccessMulti-camera panoramic imaging system calibration(2019-01) Jarron, David; Lichti, Derek D.; Shahbazi, Mozhdeh M.; Radovanovic, Robert S.A mobile mapping system (MMS) is a three-dimensional reality capture system that collects georeferenced spatial data with integrated navigation and imaging sensors from a moving vehicle. Several imaging subsystems can be found on board an MMS, such as panoramic camera systems and LiDAR sensors. The data collected from a panoramic imaging system must be accurately georeferenced and the sensors must be rigorously calibrated to ensure accurate registration of images to the point clouds collected by the LiDAR sensors, and to ensure panoramic images are generated seamlessly. The panoramic imaging system studied in this work is the Ladybug5 (by FLIR Integrated Imaging Solutions), which is a spherical camera system comprised of six individual wide-angle cameras. Having accurate estimates of the interior and relative orientation parameters of these cameras is essential for integrating the camera system with other sensors in the MMS to generate georeferenced spatial data. However, field experience has shown that factory-provided calibrations may be insufficiently accurate for high-precision applications. An investigation of the geometric calibration of the Ladybug 5 system was conducted in a dedicated indoor calibration facility at the University of Calgary: an 11 m x 11 m x 4 m field comprising 291 signalized photogrammetry targets. Multiple free-network, self-calibrating bundle adjustments were performed using different sets of constraints to model several systematic error sources. Weighted constraints were included in the adjustment to enforce the stability of the six relative orientation parameters between image pairs, and separate colour channel adjustments were used to compensate for chromatic aberrations. The overall fit of observations to the calibration model as measured by the root mean square error of the image point residuals was at the level of 0.3-0.4 pixels. Mean object point precision was at the 0.3 mm level. Rectified and ortho-rectified panoramas were also generated to verify the calibrations precision and observe how adjustments with constraints effect panorama generation.