Hierarchical Hardware/Software Algorithm for Multi-view Object Reconstruction by 3D Point Clouds Matching

The Matching or Registration of 3D point clouds is a problem that arises in a variety of research areas with applications ranging from heritage reconstruction to quality control of precision parts in industrial settings. The central problem in this research area is that of receiving two point clouds, usually representing different parts of the same object and finding the best possible rigid alignment between them. Noise in data, a varying degree of overlap and different data acquisition devices make this a complex problem with a high computational cost. This issue is sometimes addressed by adding hardware to the scanning system, but this hardware is frequently expensive and bulky. We present an algorithm that makes use of cheap, widely available (smartphone) sensors to obtain extra information during data acquisition. This information then allows for fast software registration. The first such hybrid hardware-software approach was presented in [31]. In this paper we improve the performance of this algorithm by using hierarchical techniques. Experimental results using real data show how the algorithm presented greatly improves the computation time of the previous algorithm and compares favorably to state of the art algorithms.