The comparison of single view calibration methods
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In order to resolve interior parameters of camera geometry there have been numerous development projects to automate the process. In photogrammetric community the problem solution has been sought by using coded targets and applying non-linear model in order to find accurate values for interior camera parameters. An alternative approach, popular especially in computer vision applications has been to discard the targeting and use existing geometric properties of scene to solve intrinsic parameters instead i.e. parallel lines and orthogonality of line sets. However, in most cases the parameters to be solved have been restricted to linear components of camera model. In this paper we compare the accuracy of two alternative single view calibration approaches with results from multi-station multi-image calibration. The idea is to study the accuracy and reliability of alternative mathematical models to solve intrinsic camera parameters from single view geometry.
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