用三维标记点迭代校准多相机，提升3D重建精度
Marker-Based Extrinsic Calibration Method for Accurate Multi-Camera 3D Reconstruction
- 基于三维标记点的几何约束，通过聚类与迭代优化实现校准
- 实验显示对齐误差显著降低，支持真实场景下高精度重建
- 适合需要精准多视角3D建模的应用，如医疗营养追踪
使用多相机RGB-D系统进行精确3D重建，关键在于相机间外参的准确标定以实现视图间的正确对齐。本文提出一种基于三维标记点的迭代外参校准方法，利用其提供的几何约束显著提升校准精度。该方法通过聚类、回归分析和迭代重分配技术，系统性地分割并优化标记平面，确保各相机视角间的鲁棒几何对应关系。我们在受控环境及实际应用（科技饮食项目）中全面验证了该方法，实验结果表明对齐误差大幅减少，从而实现了准确可靠的3D重建。
原文摘要 · Abstract (English)
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.
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