Improved Calibration for Panoramic Annular Lens Systems with Angular Modulation

This paper addresses the challenges of calibrating Panoramic Annular Lens (PAL) systems, which exhibit unique projection characteristics due to their imaging relationship designed to compress blind zones. Traditional camera calibration methods often fail to accurately capture these properties. To resolve this limitation, we propose a novel projection model that incorporates angular modulation, enabling a more accurate representation of the PAL system’s imaging process. This formulation significantly improves the model’s ability to describe the relationship between object space and image space. We evaluate our approach on both synthetic and real-world datasets tailored for PAL cameras. Experimental results demonstrate that the model achieves sub-pixel accuracy, with reprojection errors typically ranging from 0. 1 to 0. 3 pixels on 2048×2048 images when using five distortion terms. This level of precision surpasses existing calibration models for panoramic cameras, making our method particularly suitable for high-accuracy applications. The datasets used in this study are publicly available at https://github.com/wwendy233/PALcalib.

Authors

• Ding Wang
• Junhua Wang
• Yuhan Tian
• Min Xu
• Lingbao Kong

Keywords

• Visualization
• Solid modeling
• Accuracy
• Three-dimensional displays
• Robot vision systems
• Cameras
• Distortion
• Distance measurement
• Calibration
• Lenses
• Angular Modes
• Model Calibration
• Image Space
• Calibration Method
• Model Projections
• Objective Space
• Reprojection Error
• Sub-pixel Accuracy
• Perturbation Theory
• Focal Length
• Nonlinear Programming
• Image Distortion
• Numerical Stability
• Calibration Results
• Tangential Direction
• Tangential Components
• Calibration Time
• Optical Design
• Dataset S1
• Image Calibration
• Distortion Model
• Calibration Performance
• Camera Features