Superaccurate camera calibration via inverse rendering

Morten Hannemose; Jakob Wilm; Jeppe Revall Frisvad

doi:10.1117/12.2531769

21 June 2019 Superaccurate camera calibration via inverse rendering

Morten Hannemose, Jakob Wilm, Jeppe Revall Frisvad

Proceedings Volume 11057, Modeling Aspects in Optical Metrology VII; 1105717 (2019) https://doi.org/10.1117/12.2531769
Event: SPIE Optical Metrology, 2019, Munich, Germany

Abstract

The most prevalent routine for camera calibration is based on the detection of well-defined feature points on a purpose-made calibration artifact. These could be checkerboard saddle points, circles, rings or triangles, often printed on a planar structure. The feature points are first detected and then used in a nonlinear optimization to estimate the internal camera parameters. We propose a new method for camera calibration using the principle of inverse rendering. Instead of relying solely on detected feature points, we use an estimate of the internal parameters and the pose of the calibration object to implicitly render a non-photorealistic equivalent of the optical features. This enables us to compute pixel-wise differences in the image domain without interpolation artifacts. We can then improve our estimate of the internal parameters by minimizing pixel-wise least-squares differences. In this way, our model optimizes a meaningful metric in the image space assuming normally distributed noise characteristic for camera sensors. We demonstrate using synthetic and real camera images that our method improves the accuracy of estimated camera parameters as compared with current state-of-the-art calibration routines. Our method also estimates these parameters more robustly in the presence of noise and in situations where the number of calibration images is limited.

Conference Presentation

Citation Download Citation

Morten Hannemose, Jakob Wilm, and Jeppe Revall Frisvad "Superaccurate camera calibration via inverse rendering", Proc. SPIE 11057, Modeling Aspects in Optical Metrology VII, 1105717 (21 June 2019); https://doi.org/10.1117/12.2531769

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