Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration Article Swipe
Oleksandr Yuhai
,
Yubin Cho
,
Ahnryul Choi
,
Joung Hwan Mun
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/photonics11090867
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/photonics11090867
The accurate transformation of multi-camera 2D coordinates into 3D coordinates is critical for applications like animation, gaming, and medical rehabilitation. This study unveils an enhanced multi-camera calibration method that alleviates the shortcomings of existing approaches by incorporating a comprehensive cost function and Adaptive Iteratively Reweighted Least Squares (AIRLS) optimization. By integrating static error components (3D coordinate, distance, angle, and reprojection errors) with dynamic wand distance errors, the proposed comprehensive cost function facilitates precise multi-camera parameter calculations. The AIRLS optimization effectively balances the optimization of both static and dynamic error elements, enhancing the calibration’s robustness and efficiency. Comparative validation against advanced multi-camera calibration methods shows this method’s superior accuracy (average error 0.27 ± 0.22 mm) and robustness. Evaluation metrics including average distance error, standard deviation, and range (minimum and maximum) of errors, complemented by statistical analysis using ANOVA and post-hoc tests, underscore its efficacy. The method markedly enhances the accuracy of calculating intrinsic, extrinsic, and distortion parameters, proving highly effective for precise 3D reconstruction in diverse applications. This study represents substantial progression in multi-camera calibration, offering a dependable and efficient solution for intricate calibration challenges.
Related Topics
Concepts
Computer science
Robustness (evolution)
Calibration
Computer vision
Artificial intelligence
Iteratively reweighted least squares
Reprojection error
Rigid transformation
Mean squared error
Algorithm
Mathematics
Total least squares
Singular value decomposition
Statistics
Gene
Biochemistry
Chemistry
Image (mathematics)
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/photonics11090867
- OA Status
- gold
- Cited By
- 1
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402614993
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4402614993Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/photonics11090867Digital Object Identifier
- Title
-
Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error IntegrationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-15Full publication date if available
- Authors
-
Oleksandr Yuhai, Yubin Cho, Ahnryul Choi, Joung Hwan MunList of authors in order
- Landing page
-
https://doi.org/10.3390/photonics11090867Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3390/photonics11090867Direct OA link when available
- Concepts
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Computer science, Robustness (evolution), Calibration, Computer vision, Artificial intelligence, Iteratively reweighted least squares, Reprojection error, Rigid transformation, Mean squared error, Algorithm, Mathematics, Total least squares, Singular value decomposition, Statistics, Gene, Biochemistry, Chemistry, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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