Fixed Relative Pose Prior for Camera Array Self-Calibration

Abstract

Camera arrays have unique advantages in various computer vision tasks, such as 3D scene reconstruction and depth estimation. For these tasks, precise calibration of sub-cameras is crucial. Since the baselines of sub-cameras are usually small, it is challenging to calibrate the camera array through a single recording of the scene. Consequently, the majority of existing calibration methods address this issue by recording a scene at different spatial locations. However, this approach neglects the prior that the relative pose of the sub-cameras remains unchanged across different locations, which leads to an increase in cumulative reprojection errors. In this letter, we propose to incorporate this fixed relative pose prior to precisely calibrate the camera array. Specifically, we first capture dual-array frames by recording a scene at two spatial locations. Then, we incorporate the fixed relative pose prior to the camera array calibration process by integrating the linear constraint into the organization of sub-aperture images (SAIs). Our method maintains the minimum necessary degrees of freedom for the calibration model, and reduces cumulative reprojection error. Moreover, we develop a real-world light field dataset for comprehensive performance evaluation. Experimental results demonstrate that our method can achieve higher calibration accuracy as compared to existing methods. Our code and dataset are available at https://github.com/Zhangyaning-NUDT/Fixed-relative-pose-prior-for-camera-array-self-calibration.