Calibration-Free Structure-from-Motion with Calibrated Radial Trifocal Tensors

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Abstract

In this paper we consider the problem of Structure-from-Motion from images with unknown intrinsic calibration. Instead of estimating the internal camera parameters through some self-calibration procedure, we propose to use a subset of the reprojection constraints that is invariant to radial displacement. This allows us to recover metric 3D reconstructions without explicitly estimating the cameras’ focal length or radial distortion parameters. The weaker projection model makes initializing the reconstruction especially difficult. To handle this additional challenge we propose two novel minimal solvers for radial trifocal tensor estimation. We evaluate our approach on real images and show that even for extreme optical systems, such as fisheye or catadioptric, we are able to get accurate reconstructions without performing any calibration.

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Larsson, V., Zobernig, N., Taskin, K., & Pollefeys, M. (2020). Calibration-Free Structure-from-Motion with Calibrated Radial Trifocal Tensors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12350 LNCS, pp. 382–399). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58558-7_23

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