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Computer Science > Computer Vision and Pattern Recognition

arXiv:2203.04661 (cs)
[Submitted on 9 Mar 2022]

Title:Creating Realistic Ground Truth Data for the Evaluation of Calibration Methods for Plenoptic and Conventional Cameras

Authors:Tim Michels, Arne Petersen, Reinhard Koch
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Abstract:Camera calibration methods usually consist of capturing images of known calibration patterns and using the detected correspondences to optimize the parameters of the assumed camera model. A meaningful evaluation of these methods relies on the availability of realistic synthetic data. In previous works concerned with conventional cameras the synthetic data was mainly created by rendering perfect images with a pinhole camera and subsequently adding distortions and aberrations to the renderings and correspondences according to the assumed camera model. This method can bias the evaluation since not every camera perfectly complies with an assumed model. Furthermore, in the field of plenoptic camera calibration there is no synthetic ground truth data available at all. We address these problems by proposing a method based on backward ray tracing to create realistic ground truth data that can be used for an unbiased evaluation of calibration methods for both types of cameras.
Comments: 9 pages, 8 figures. Accepted at 3DV 2019
Subjects: Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR)
Cite as: arXiv:2203.04661 [cs.CV]
  (or arXiv:2203.04661v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2203.04661
Journal reference: 2019 International Conference on 3D Vision (3DV). IEEE, 2019
Related DOI: https://doi.org/10.1109/3DV.2019.00055

Submission history

From: Tim Michels [view email]
[v1] Wed, 9 Mar 2022 11:58:00 UTC (3,877 KB)
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