Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration
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 co...
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MDPI AG
2024-09-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/11/9/867 |
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| author | Oleksandr Yuhai Yubin Cho Ahnryul Choi Joung Hwan Mun |
| author_facet | Oleksandr Yuhai Yubin Cho Ahnryul Choi Joung Hwan Mun |
| author_sort | Oleksandr Yuhai |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ea5cb8fc507948bdb45ab91acfbfed35 |
| institution | OA Journals |
| issn | 2304-6732 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj-art-ea5cb8fc507948bdb45ab91acfbfed352025-08-20T01:55:46ZengMDPI AGPhotonics2304-67322024-09-0111986710.3390/photonics11090867Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error IntegrationOleksandr Yuhai0Yubin Cho1Ahnryul Choi2Joung Hwan Mun3Department of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, Suwon 16419, Republic of KoreaDepartment of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, Suwon 16419, Republic of KoreaDepartment of Biomedical Engineering, College of Medicine, Chungbuk National University, Cheongju 28644, Republic of KoreaDepartment of Bio-Mechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, Suwon 16419, Republic of KoreaThe 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.https://www.mdpi.com/2304-6732/11/9/867multi-camera calibrationcomprehensive cost functioncamera parameters optimizationadaptive iteratively reweighted least squaresmotion capture |
| spellingShingle | Oleksandr Yuhai Yubin Cho Ahnryul Choi Joung Hwan Mun Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration Photonics multi-camera calibration comprehensive cost function camera parameters optimization adaptive iteratively reweighted least squares motion capture |
| title | Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration |
| title_full | Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration |
| title_fullStr | Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration |
| title_full_unstemmed | Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration |
| title_short | Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration |
| title_sort | enhanced three axis frame and wand based multi camera calibration method using adaptive iteratively reweighted least squares and comprehensive error integration |
| topic | multi-camera calibration comprehensive cost function camera parameters optimization adaptive iteratively reweighted least squares motion capture |
| url | https://www.mdpi.com/2304-6732/11/9/867 |
| work_keys_str_mv | AT oleksandryuhai enhancedthreeaxisframeandwandbasedmulticameracalibrationmethodusingadaptiveiterativelyreweightedleastsquaresandcomprehensiveerrorintegration AT yubincho enhancedthreeaxisframeandwandbasedmulticameracalibrationmethodusingadaptiveiterativelyreweightedleastsquaresandcomprehensiveerrorintegration AT ahnryulchoi enhancedthreeaxisframeandwandbasedmulticameracalibrationmethodusingadaptiveiterativelyreweightedleastsquaresandcomprehensiveerrorintegration AT jounghwanmun enhancedthreeaxisframeandwandbasedmulticameracalibrationmethodusingadaptiveiterativelyreweightedleastsquaresandcomprehensiveerrorintegration |