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Authors: Yingna Su 1 ; 2 ; Xinnian Guo 1 ; 2 and Yang Shen 3

Affiliations: 1 College of Information Engineering, Suqian University, Suqian, China ; 2 Suqian Key Laboratory of Visual Inspection and Intelligent Control, Suqian University, Suqian, China ; 3 Industrial Technology Research Institute, Suqian University, Suqian, China

Keyword(s): Camera Self-Calibration, Gravity Direction, Homography Constraints, Principal Point Estimation.

Abstract: Camera calibration is crucial for enabling accurate and robust visual perception. This paper addresses the challenge of recovering intrinsic camera parameters from two views of a planar surface, that has received limited attention due to its inherent degeneracy. For cameras equipped with Inertial Measurement Units (IMUs), such as those in smartphones and drones, the camera’s y-axes can be aligned with the gravity direction, reducing the relative orientation to a one-degree-of-freedom (1-DoF). A key insight is the general orthogonality between the ground plane and the gravity direction. Leveraging this ground plane constraint, the paper introduces new homography-based minimal solutions for camera self-calibration with a known gravity direction. we derive 2.5- and 3.5-point camera self-calibration algorithms for points in the ground plane to enable simultaneous estimation of the camera’s focal length and principal point. The paper demonstrates the practicality and efficiency of these a lgorithms and comparisons to existing state-of-the-art methods, confirming their reliability under various levels of noise and different camera configurations. (More)

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Paper citation in several formats:
Su, Y., Guo, X. and Shen, Y. (2024). Camera Self-Calibration from Two Views with a Common Direction. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 680-685. DOI: 10.5220/0012438100003660

@conference{visapp24,
author={Yingna Su and Xinnian Guo and Yang Shen},
title={Camera Self-Calibration from Two Views with a Common Direction},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={680-685},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012438100003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Camera Self-Calibration from Two Views with a Common Direction
SN - 978-989-758-679-8
IS - 2184-4321
AU - Su, Y.
AU - Guo, X.
AU - Shen, Y.
PY - 2024
SP - 680
EP - 685
DO - 10.5220/0012438100003660
PB - SciTePress