Hand-guided 3D surface acquisition by combining simple light sectioning with real-time algorithms
Hand-guided 3D surface acquisition by combining simple light sectioning with real-time algorithms
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发表时间：
2014-01
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通讯作者：
O. Arold;S. Ettl;F. Willomitzer;G. Häusler
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作者：
O. Arold;S. Ettl;F. Willomitzer;G. Häusler
刚性表面的精确3D测量在许多应用领域（如质量控制或外科手术）中是期望的。通常，必须获取来自对象周围的所有视图以用于对象表面的完整3D描述。我们提出了一个传感器的原则，称为“飞行三角测量”，避免了一个复杂的“走走停停”的过程。它结合了一个低成本的经典光节传感器与算法流水线。一个手动引导的传感器在物体周围移动的同时捕捉3D视图的连续电影。视图会自动对齐，并真实的显示采集的3D模型。与大多数现有的传感器相比，没有带宽被浪费用于投影线的空间或时间编码。3D采集也不需要昂贵的彩色相机。所生成的3D数据的可实现的测量不确定性和横向分辨率仅受物理限制。垂直线和水平线的交替投影保证了连续3D视图中对应点的存在。这使得能够在没有表面插值的情况下精确配准。对于注册，迭代最近点算法的一个变种-适应我们的3D视图的特定性质-被引入。此外，数据减少和平滑，而不损失横向分辨率，以及获取和映射的彩色纹理。仿真和测量结果表明了该传感器的精度和适用性。
Precise 3D measurements of rigid surfaces are desired in many fields of application like quality control or surgery. Often, views from all around the object have to be acquired for a full 3D description of the object surface. We present a sensor principle called "Flying Triangulation" which avoids an elaborate "stop-and-go" procedure. It combines a low-cost classical light-section sensor with an algorithmic pipeline. A hand-guided sensor captures a continuous movie of 3D views while being moved around the object. The views are automatically aligned and the acquired 3D model is displayed in real time. In contrast to most existing sensors no bandwidth is wasted for spatial or temporal encoding of the projected lines. Nor is an expensive color camera necessary for 3D acquisition. The achievable measurement uncertainty and lateral resolution of the generated 3D data is merely limited by physics. An alternating projection of vertical and horizontal lines guarantees the existence of corresponding points in successive 3D views. This enables a precise registration without surface interpolation. For registration, a variant of the iterative closest point algorithm - adapted to the specific nature of our 3D views - is introduced. Furthermore, data reduction and smoothing without losing lateral resolution as well as the acquisition and mapping of a color texture is presented. The precision and applicability of the sensor is demonstrated by simulation and measurement results.