Xueyan Tang’s scientific contributions

This article introduces a multiview 3-D microscopic profilometry system equipped with tilted cameras adhering to the Scheimpflug condition and a vertically aligned projector. It utilizes a novel 3-D cross-ratio invariant (3D-CRI) model that offers inherent self-correction, enhanced global consistency, and computational efficiency. The inherent self-correction mitigates optical contaminations like multiple reflections by using deviations from the epipolar line for optimal candidate selection. The model is also designed as spatial lines to associate the approximate linear error distribution across depths, thereby facilitating its further correction (e.g., proposed embedded linear compensation method to address data inconsistency among various binocular projector-camera setups). Additionally, the model simplifies computational demands by directly correlating phase differences to spatial coordinates. Furthermore, a conversion method from the triangular stereo to the 3D-CRI model is developed, avoiding the complex per-pixel calibration. The experiments are conducted to verify robustness, globally consistent accuracy, and speed performance. The experimental results validate that the system is robust to multiple reflections by testing on the printed circuit boards with dense components. The global consistency is also verified by the experiments with better quantitative metrics within the whole measurement range over ten times the depth of field. In particular, the quantitative metrics of the Z -axis are halved. The speed performance shows that our method is the fastest among competing techniques.

This article proposes a novel calibration framework for a multiview microscopic 3-D measurement system comprising multiple tilted-cameras with the Scheimpflug condition and one vertical projector. Conventionally, the accurate and independent point correspondences between images and planar targets achieve successful calibration. However, affected by our system's large imaging magnification and anisotropic perspectivity, targets’ poses must be limited in the shallow common focus volume to ensure correspondences’ extracting accuracy of all views. This imaging constraint will lead to insufficiently independent correspondences in calibration computation, where constraints will be insufficient in parameter estimation (under-constraint problems) and bundle adjustment (falling in local optima caused by ambiguous models). To this end, our method first relies on insufficiently independent correspondences to tackle the above problems. In calibrating multiple tilted-cameras, the proposed initialization method incorporates the lens equation as an additional constraint to solve the under-constraint problem. The subsequent multicamera bundle adjustment disambiguates by stereo constraints. Moreover, for the vertical projector, another novel unconventional calibration method utilizes geometric constraints to determine its projection matrix. The experiments prove that the estimation and optimization of parameters for multiple tilted-cameras are significantly enhanced with the smallest reprojection error near 0.1 pixel. In addition, the 3-D measurement result of the standard concentric cylinders has also been applied to demonstrate the accuracy of the vertical projector calibration and the whole calibration framework.