He Kejing, Sui Congying, Huang Tianyu, Zhang Yiyun, Zhou Weiguo, Chen Xing, Liu Yun-Hui
Opt Express. 2022 Mar 14;30(6):8571-8591. doi: 10.1364/OE.449300.
Acquiring the 3D geometry of objects has been an active research topic, wherein the reconstruction of transparent objects poses a great challenge. In this paper, we present a fully automatic approach for reconstructing the exterior surface of a complex transparent scene. Through scanning a line laser by a galvo-mirror, images of the scene are captured from two viewing directions. Due to the light transmission inside the transparent object, the captured feature points and the calibrated laser plane can produce large number of 3D point candidates with large incorrect points through direct triangulation. Various situations of laser transmission inside the transparent object are analyzed and the reconstructed 3D laser point candidates are classified into two types: first-reflection points and non-first-reflection points. The first-reflection points means the first reflected laser points on the front surface of measured objects. Then, a novel four-layers refinement process is proposed to extract the first-reflection points step by step from the 3D point candidates through optical geometric constraints, including (1) Layer-1 : fake points removed by single camera, (2) Layer-2 : ambiguity points removed by the dual-camera joint constraint, (3) Layer-3 : retrieve the missing first-reflection exterior surface points by fusion and (4) Layer-4 : severe ambiguity points removed by contour-continuity. Besides, a novel calibration model about this imaging system is proposed for 3D point candidates reconstruction through triangulation. Compared with traditional laser scanning method, we pulled in the viewing angle information of the second camera and a novel four-layers refinement process is adopted for reconstruction of transparent objects. Various experiments on real objects demonstrate that proposed method can successfully extract the first-reflection points from the candidates and recover the complex shapes of transparent and semitransparent objects.
获取物体的三维几何形状一直是一个活跃的研究课题，其中透明物体的重建面临着巨大挑战。在本文中，我们提出了一种全自动方法来重建复杂透明场景的外表面。通过振镜扫描线激光，从两个观察方向捕获场景图像。由于透明物体内部的光传输，通过直接三角测量，捕获的特征点和校准后的激光平面会产生大量包含大量错误点的三维点候选。分析了透明物体内部激光传输的各种情况，并将重建的三维激光点候选分为两类：首次反射点和非首次反射点。首次反射点是指在被测物体前表面上首次反射的激光点。然后，提出了一种新颖的四层细化过程，通过光学几何约束从三维点候选中逐步提取首次反射点，包括：（1）第一层：通过单相机去除假点；（2）第二层：通过双相机联合约束去除模糊点；（3）第三层：通过融合找回缺失的首次反射外表面点；（4）第四层：通过轮廓连续性去除严重模糊点。此外，还提出了一种关于该成像系统的新颖校准模型，用于通过三角测量重建三维点候选。与传统激光扫描方法相比，我们引入了第二个相机的视角信息，并采用新颖的四层细化过程来重建透明物体。对真实物体进行的各种实验表明，所提出的方法能够成功地从候选点中提取首次反射点，并恢复透明和半透明物体的复杂形状。
