Dynamic 3D shape reconstruction under complex reflection and transmission conditions using multi-scale parallel single-pixel imaging

Depth measurement and three-dimensional(3D)imaging under complex reflection and transmission conditions are challenging and even impossible for traditional structured light techniques,owing to the precondition of point-to-point triangulation.Despite recent progress in addressing this problem,there is still no efficient and general solution.Herein,a Fourier dual-slice projection with depth-constrained localization is presented to separate and utilize different illumination and reflection components efficiently,which can significantly decrease the number of projection patterns in each sequence from thousands to fifteen.Subsequently,multi-scale parallel single-pixel imaging(MS-PSI)is proposed based on the established and proven position-invariant theorem,which breaks the local regional assumption and enables dynamic 3D reconstruction.Our methodology successfully unveils unseen-before capabilities such as(1)accurate depth measurement under interreflection and subsurface scattering conditions,(2)dynamic measurement of the time-varying high-dynamic-range scene and through thin volumetric scattering media at a rate of 333 frames per second;(3)two-layer 3D imaging of the semitransparent surface and the object hidden behind it.The experimental results confirm that the proposed method paves the way for dynamic 3D reconstruction under complex optical field reflection and transmission conditions,benefiting imaging and sensing applications in advanced manufacturing,autonomous driving,and biomedical imaging.

3D Surface Reconstruction of Coarse Aggregate Particles from Occlusion-Free Multi-View Images

Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.