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

2025-02-13

AI Summary

Addressing the challenge of efficient and robust calibration of PTZ cameras under arbitrary viewing angles, this paper proposes a two-stage calibration framework. In the offline stage, we introduce a novel PTZ Incremental Bundle Adjustment (PTZ-IBA) algorithm that automatically estimates multi-view intrinsic and extrinsic parameters within a local coordinate system, while enabling end-to-end alignment with the geographic coordinate system. In the online stage, calibrating a new viewpoint is formulated as a relocalization problem, integrating 3D–2D feature matching with coordinate-system optimization to balance accuracy and real-time performance. Our method synergistically combines multi-view geometry with incremental optimization. Extensive experiments on diverse real-world and synthetic datasets demonstrate significant improvements over state-of-the-art methods in both accuracy and robustness, with strong generalization across varying scenes and camera configurations. The source code and benchmark datasets are publicly released.

Technology Category

• Computer Vision: Motion & Tracking
• Intelligent Robots: Localization, Mapping, and Navigation
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

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

Problem

• Robust PTZ camera calibration method
• Efficient camera parameter estimation
• Balances accuracy and computational efficiency

Innovation

• Two-stage PTZ camera calibration
• PTZ-IBA algorithm usage
• Online viewpoint relocalization