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Automated Registration of 3D Scans Using Geometric Features and Normalized Color Data

机译：使用几何特征和归一化颜色数据自动注册3D扫描

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摘要

Laser range sensors are playing an increased role in construction. These devices are used to collect a large number of points from different locations and then, those points are registered in a common framework. This article describes a new procedure for the registration of point clouds, especially suited to the fields of architecture and cultural heritage. Often, in these fields, the registration of point clouds is subject to errors due to the fact that an important number of points do not lie on particular geometric features. In this article, an accurate and efficient approach for 3D data registration based on Iterative Closest Point (ICP) algorithm is proposed, which takes advantage of the color data acquired along with range data. Points suitable for registration are selected according to their local geometry and/or color properties, thus a significant improvement on performance convergence and processing time is obtained. The algorithm performs an automatic, on-the-flight estimation of the overlapping region, taking into account possible color differences produced by lighting changes through the measurement process. The proposed approach has been tested on real scanned data from cultural heritage buildings and compared to other approaches, showing a better performance in terms of automation degree, accuracy, and speed.
机译：激光测距传感器在建筑中扮演着越来越重要的角色。这些设备用于从不同位置收集大量点，然后将这些点注册在一个通用框架中。本文介绍了一种新的点云注册过程，特别适合于建筑和文化遗产领域。通常，在这些领域中，由于大量点并不位于特定的几何特征上，因此点云的配准容易出错。本文提出了一种基于迭代最近点（ICP）算法的准确，高效的3D数据配准方法，该方法利用了随距离数据一起获取的颜色数据。根据它们的局部几何形状和/或颜色属性选择适合配准的点，从而可以显着改善性能收敛和处理时间。该算法会考虑到在整个测量过程中由于照明变化而产生的可能的色差，从而对重叠区域进行自动的动态估计。该提议的方法已经过对文化遗产建筑的真实扫描数据进行测试，并与其他方法进行了比较，在自动化程度，准确性和速度方面显示出更好的性能。

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