Wang Peng, Zhang Liyan
Appl Opt. 2020 Dec 10;59(35):10986-10994. doi: 10.1364/AO.409400.
As an accurate and efficient shape measurement method, fringe-projection-based three-dimensional (3D) reconstruction has been extensively studied. However, patchwise point cloud registration without extra assistance is still a challenging task. We present a flexible and robust self-registration shape measurement method based on fringe projection and structure from motion (SfM). Other than ordinary structured-light measurement devices in which the camera and the projector are rigidly connected together, the camera and the projector in our method can be moved independently. An image-capturing scheme and underlying image-matching strategy are proposed. By selectively utilizing some sparse correspondence points across the fringe images as virtual markers, the global positions of the camera and the projector corresponding to each image are calculated and optimized under the framework of SfM. Dense global 3D points all over the object surface are finally calculated via forward intersection. Experimental results on different objects demonstrate that the proposed method can obtain a self-registered 3D point cloud with comparable accuracy to the state-of-the-art techniques by using only one camera and one projector, requiring no post-registration procedures and no assistant markers.
作为一种精确高效的形状测量方法,基于条纹投影的三维(3D)重建已得到广泛研究。然而,在没有额外辅助的情况下进行逐块点云配准仍然是一项具有挑战性的任务。我们提出了一种基于条纹投影和运动结构(SfM)的灵活且鲁棒的自配准形状测量方法。与相机和投影仪刚性连接在一起的普通结构光测量设备不同,我们方法中的相机和投影仪可以独立移动。提出了一种图像采集方案和底层图像匹配策略。通过有选择地利用条纹图像中的一些稀疏对应点作为虚拟标记,在SfM框架下计算并优化与每个图像对应的相机和投影仪的全局位置。最终通过前方交会计算出物体表面的密集全局3D点。在不同物体上的实验结果表明,该方法仅使用一个相机和一个投影仪就能获得与现有技术精度相当的自配准3D点云,无需后配准程序和辅助标记。