Marker-Based Extrinsic Calibration Method for Accurate Multi-Camera 3D Reconstruction

TL;DR

This paper presents an iterative marker-based extrinsic calibration method that enhances multi-camera 3D reconstruction accuracy by leveraging geometric constraints and robust segmentation techniques, validated in controlled and real-world environments.

Contribution

The proposed approach introduces a novel iterative calibration method using 3D markers, improving accuracy over existing techniques in multi-camera systems.

Findings

Significant reduction in alignment errors

Improved 3D reconstruction accuracy

Validated in real-world clinical settings

Abstract

Accurate 3D reconstruction using multi-camera RGB-D systems critically depends on precise extrinsic calibration to achieve proper alignment between captured views. In this paper, we introduce an iterative extrinsic calibration method that leverages the geometric constraints provided by a three-dimensional marker to significantly improve calibration accuracy. Our proposed approach systematically segments and refines marker planes through clustering, regression analysis, and iterative reassignment techniques, ensuring robust geometric correspondence across camera views. We validate our method comprehensively in both controlled environments and practical real-world settings within the Tech4Diet project, aimed at modeling the physical progression of patients undergoing nutritional treatments. Experimental results demonstrate substantial reductions in alignment errors, facilitating accurate and reliable 3D reconstructions.