English

PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration

Computer Vision and Pattern Recognition 2025-02-14 v1

Abstract

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{\deg} 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

Keywords

Cite

@article{arxiv.2502.09075,
  title  = {PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration},
  author = {Jinhui Guo and Lubin Fan and Bojian Wu and Jiaqi Gu and Shen Cao and Jieping Ye},
  journal= {arXiv preprint arXiv:2502.09075},
  year   = {2025}
}

Comments

Accepted by ICRA 2025

R2 v1 2026-06-28T21:42:45.428Z