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Two-stage automated measurement process for high-resolution 3D digitization of unknown objects

机译:两阶段自动测量过程,可对未知对象进行高分辨率3D数字化

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In this paper, a process for high-resolution, automated 3D digitization of unknown objects (i.e., without any digital model) is presented. The process has two stages-the first leads to a coarse 3D digital model of the object, and the second obtains the final model. A rough model, acquired by a 3D measurement head with a large working volume and relatively low resolution, is used to calculate the precise head positions required for the full digitization of the object, as well as collision detection and avoidance. We show that this approach is much more efficient than digitization with only a precise head, when its positions for subsequent measurements (so-called next-best-views) must be calculated based only on a partially recovered 3D model of the object. We also show how using a rough object representation for collision detection shortens the high-resolution digitization process. (C) 2016 Optical Society of America
机译:在本文中,提出了一种对未知对象(即没有任何数字模型)进行高分辨率,自动3D数字化的过程。该过程分为两个阶段,第一个阶段产生对象的粗略3D数字模型,第二个阶段获得最终模型。由具有大工作量和相对较低分辨率的3D测量头获取的粗略模型用于计算对象的完全数字化以及碰撞检测和避免所需的精确头位置。我们证明了这种方法比仅使用精确头部的数字化方法要有效得多,因为仅根据部分恢复的对象3D模型来计算其后续测量位置(所谓的最佳视图)。我们还展示了使用粗略的对象表示进行碰撞检测如何缩短高分辨率的数字化过程。 (C)2016美国眼镜学会

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