Automated Calibration of Mobile Cameras for 3D Reconstruction of Mechanical Pipes

TL;DR

This paper introduces a novel calibration framework for mobile cameras using large-scale circular targets, significantly improving 3D reconstruction accuracy of mechanical pipes with robust target matching and eccentricity correction.

Contribution

The work presents new methods for target matching, eccentricity error adjustment, and iterative self-calibration, enhancing mobile camera calibration for 3D pipe reconstruction.

Findings

Robust target matching in 270 mobile images

Eccentricity correction comparable to closed-form solutions

Approximately 45% improvement in 3D radius estimation accuracy

Abstract

This manuscript provides a new framework for calibration of optical instruments, in particular mobile cameras, using large-scale circular black and white target fields. New methods were introduced for (i) matching targets between images; (ii) adjusting the systematic eccentricity error of target centers; and (iii) iteratively improving the calibration solution through a free-network self-calibrating bundle adjustment. It was observed that the proposed target matching effectively matched circular targets in 270 mobile phone images from a complete calibration laboratory with robustness to Type II errors. The proposed eccentricity adjustment, which requires only camera projective matrices from two views, behaved synonymous to available closed-form solutions, which require several additional object space target information a priori. Finally, specifically for the case of the mobile devices, the calibration parameters obtained using our framework was found superior compared to in-situ calibration for estimating the 3D reconstructed radius of a mechanical pipe (approximately 45% improvement).