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Radial Distortion Invariant Factorization for Structure From Motion

Factorization methods are frequently used for structure from motion problems (SfM). In the presence of noise they are able to jointly estimate camera matrices and scene points in overdetermined settings, without the need for accurate initial solutions. While the early formulations were restricted to affine models, recent approaches have been show to work with pinhole cameras by minimizing object space errors. In this paper we propose a factorization approach using the so called radial camera, which is invariant to radial distortion and changes in focal length. Assuming a known principal point our approach can reconstruct the 3D scene in settings with unknown and varying radial distortion and focal length. We show on both real and synthetic data that our approach outperforms state-of-the-art factorization methods under these conditions.

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