PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866913689287786496 |
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| author | Guo, Jinhui Fan, Lubin Wu, Bojian Gu, Jiaqi Cao, Shen Ye, Jieping |
| author_facet | Guo, Jinhui Fan, Lubin Wu, Bojian Gu, Jiaqi Cao, Shen Ye, Jieping |
| contents | In this paper, we present PTZ-Calib, a robust two-stage PTZ camera calibration method, that efficiently and accurately estimates camera parameters for arbitrary viewpoints. Our method includes an offline and an online stage. In the offline stage, we first uniformly select a set of reference images that sufficiently overlap to encompass a complete 360° view. We then utilize the novel PTZ-IBA (PTZ Incremental Bundle Adjustment) algorithm to automatically calibrate the cameras within a local coordinate system. Additionally, for practical application, we can further optimize camera parameters and align them with the geographic coordinate system using extra global reference 3D information. In the online stage, we formulate the calibration of any new viewpoints as a relocalization problem. Our approach balances the accuracy and computational efficiency to meet real-world demands. Extensive evaluations demonstrate our robustness and superior performance over state-of-the-art methods on various real and synthetic datasets. Datasets and source code can be accessed online at https://github.com/gjgjh/PTZ-Calib |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_09075 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration Guo, Jinhui Fan, Lubin Wu, Bojian Gu, Jiaqi Cao, Shen Ye, Jieping Computer Vision and Pattern Recognition In this paper, we present PTZ-Calib, a robust two-stage PTZ camera calibration method, that efficiently and accurately estimates camera parameters for arbitrary viewpoints. Our method includes an offline and an online stage. In the offline stage, we first uniformly select a set of reference images that sufficiently overlap to encompass a complete 360° view. We then utilize the novel PTZ-IBA (PTZ Incremental Bundle Adjustment) algorithm to automatically calibrate the cameras within a local coordinate system. Additionally, for practical application, we can further optimize camera parameters and align them with the geographic coordinate system using extra global reference 3D information. In the online stage, we formulate the calibration of any new viewpoints as a relocalization problem. Our approach balances the accuracy and computational efficiency to meet real-world demands. Extensive evaluations demonstrate our robustness and superior performance over state-of-the-art methods on various real and synthetic datasets. Datasets and source code can be accessed online at https://github.com/gjgjh/PTZ-Calib |
| title | PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2502.09075 |