Optimal Pose Guidance for Stereo Calibration in 3D Deformation Measurement

2025-11-23

AI Summary

To address the lack of optimal camera pose guidance in stereo calibration—resulting in low efficiency and insufficient accuracy for 3D deformation measurement—this paper proposes an interactive, joint extrinsic parameter optimization calibration framework. The method innovatively formulates a unified objective function integrating both relative and absolute extrinsic parameters, employing trace minimization of the covariance matrix as the optimization criterion to automatically recommend highly informative calibration poses. It further integrates digital image correlation (DIC) with a graphical user interface to enable real-time pose guidance and quantitative assessment of calibration quality. Experimental results demonstrate that the framework achieves higher reprojection accuracy using fewer calibration images; thermal deformation measurements deviate by less than 2.1% from finite element simulations; and it exhibits strong robustness across multi-view configurations. Consequently, it significantly reduces reliance on user expertise and the number of required calibration images.

Technology Category

• Machine Learning: Calibration & Uncertainty Quantification
• Computer Vision: Biometrics, Face, Gesture & Pose
• Intelligent Robots: State Estimation

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Stereo optical measurement techniques, such as digital image correlation (DIC), are widely used in 3D deformation measurement as non-contact, full-field measurement methods, in which stereo calibration is a crucial step. However, current stereo calibration methods lack intuitive optimal pose guidance, leading to inefficiency and suboptimal accuracy in deformation measurements. The aim of this study is to develop an interactive calibration framework that automatically generates the next optimal pose, enabling high-accuracy stereo calibration for 3D deformation measurement. We propose a pose optimization method that introduces joint optimization of relative and absolute extrinsic parameters, with the minimization of the covariance matrix trace adopted as the loss function to solve for the next optimal pose. Integrated with this method is a user-friendly graphical interface, which guides even non-expert users to capture qualified calibration images. Our proposed method demonstrates superior efficiency (requiring fewer images) and accuracy (demonstrating lower measurement errors) compared to random pose, while maintaining robustness across varying FOVs. In the thermal deformation measurement tests on an S-shaped specimen, the results exhibit high agreement with finite element analysis (FEA) simulations in both deformation magnitude and evolutionary trends. We present a pose guidance method for high-precision stereo calibration in 3D deformation measurement. The simulation experiments, real-world experiments, and thermal deformation measurement applications all demonstrate the significant application potential of our proposed method in the field of 3D deformation measurement. Keywords: Stereo calibration, Optimal pose guidance, 3D deformation measurement, Digital image correlation

Problem

• Developing optimal pose guidance for stereo calibration in 3D deformation measurement
• Addressing inefficiency and suboptimal accuracy in current stereo calibration methods
• Creating interactive framework for high-accuracy stereo calibration with pose optimization

Innovation

• Interactive framework generates optimal calibration poses
• Joint optimization of relative and absolute extrinsic parameters
• Minimizes covariance matrix trace as loss function