Abstract
Correlation Analysis of Fish-eye Lens Camera for Acquiring Reliable Orientation Parameters
Highlights
1.1 BackgroundOwing to its characteristics, the fish-eye lens camera has been widely used for indoor and outdoor location-based services, virtual reality (VR), 3D modelling, leisure sports, and robotics.Marković et al and Caruso et al used a fish-eye lens camera for mobile robot implementation, and Sánchez et al used it for urban navigation.[1,2,3] Sreedhar et al built a system for virtual reality applications using fish-eye lens cameras.[4]
The process of determining the interior orientation parameters (IOPs) of the camera must be implemented to correct the image distortion.[8,9] The relevant previous studies can be categorized mostly into two trends: [1] the verification of each projection model of the fish-eye lens[10,11] and [2] comparisons between the projection models and the possibility of substituting a projection model.[9,12,13] Some of the previous studies found a correlation between IOPs and exterior orientation parameters (EOPs), which has rarely been analyzed in detail.[9,12,14]
The correlation analysis could be divided into two parts: (i) analysis supporting the results of previous studies, and (ii) correlation characteristics between orientation parameters observed through this research
Summary
The fish-eye lens camera has been widely used for indoor and outdoor location-based services, virtual reality (VR), 3D modelling, leisure sports, and robotics. Assistance system using multiple fish-eye lens cameras.[7] a fish-eye lens camera has a wide viewing angle, it has the disadvantage of strong geometric distortion in the image. Since the fish-eye lens camera differs from the conventional camera in the projection model equation, the way in which the correlation occurs may differ, which can have a significant impact on the parameter reliability of the fish-eye lens camera
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