Abstract
Abstract. Fisheye cameras have been widely used in photogrammetric applications, but conventional techniques must be adapted to consider specific features of fisheye images, such as nonuniform resolution in the images. This work presents experimental results of an adaptive weighting of the observation in a self-calibrating bundle adjustment to cope with the nonuniform resolution of fisheye images. GoPro Fusion and Ricoh Theta dual-fisheye systems were calibrated with bundle adjustment based on equisolid-angle projection model combined with Conrady-Brown distortion model. The image observations were weighted as a function of radial distance based on combining loss of resolution and blurring in fisheye images. The results were compared with a similar trial by considering the same standard deviation for all image observations. The use of adaptive weighting of image observations reduced the estimated standard deviation of unit weight by 30 % and 50 % with GoPro Fusion and Ricoh Theta images, respectively. The estimation of relative orientation parameters (ROPs) was also improved (∼50 %) when using adaptive weighting for image observations.
Highlights
The advantages of using 180° field of view (FoV) cameras to collect single-shot images have motivated their use in terrestrial mobile mapping and robotic applications
This paper presented an experimental analysis of dual-fisheye cameras' calibration, using different strategies for observations weighting
A black and white bar target was used to assess the magnitude of these losses and to estimate a percentage of degradation, which was used to set an adaptive weight for the observations in self-calibration adjustment, depending on the radial distance
Summary
The advantages of using 180° field of view (FoV) cameras to collect single-shot images have motivated their use in terrestrial mobile mapping and robotic applications. Areas in the image limits were discarded in the 3D reconstruction process due to the loss of resolution, generating a less noisy dense point cloud. To avoid eliminating these observations in the image limits, one alternative is to classify the fisheye image observations as a function of the image resolution, considering the image point's radial distance as a criterion. Lourenço et al (2012) and Puig et al (2014) considered different weights for the image observations as a function of the radial distance from the image centre, to describe the omnidirectional image geometry in the image matching process.
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