mlsanityData to 7 Oct 2026

Modeling dynamic target deformation in camera calibration

arXiv 2110.07322 ↗First posted 14 Oct 2021cs.CV cs.ROcited by 2

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Abstract (arXiv)

Most approaches to camera calibration rely on calibration targets of well-known geometry. During data acquisition, calibration target and camera system are typically moved w.r.t. each other, to allow image coverage and perspective versatility. We show that moving the target can lead to small temporary deformations of the target, which can introduce significant errors into the calibration result. While static inaccuracies of calibration targets have been addressed in previous works, to our knowledge, none of the existing approaches can capture time-varying, dynamic deformations. To achieve high-accuracy calibrations despite moving the target, we propose a way to explicitly model dynamic target deformations in camera calibration. This is achieved by using a low-dimensional deformation model with only few parameters per image, which can be optimized jointly with target poses and intrinsics. We demonstrate the effectiveness of modeling dynamic deformations using different calibration targets and show its significance in a structure-from-motion application.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 32 references that are in the map. First posted on arXiv 14 Oct 2021.

Builds on

5 of 32 references.

References · 5

  1. 2018The Double Sphere Camera Modelcited by 50
  2. 2019Why Having 10,000 Parameters in Your Camera Model is Better Than Twelvecited by 43
  3. 2018Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertaintycited by 15
  4. 2019Efficient Pose Selection for Interactive Camera Calibrationcited by 6
  5. 2021Inferring bias and uncertainty in camera calibrationcited by 5

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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.

2 papers.