Efficient Global Registration for Nominal/Actual Comparisons

Abstract

We investigate global registration methods for Nominal/Actual comparisons, using precise, high-resolution 3D scans. First we summarize existing approaches and requirements for this field of application. We then demonstrate that a basic RANSAC strategy, along with a slightly modified version of basic building blocks, can lead to a high global registration performance at moderate registration times. Specifically, we introduce a simple feedback loop that exploits the fast convergence of the ICP algorithm to efficiently speed up the search for a valid global alignment. Using the example of 3D printed parts and range images acquired by two different high-precision 3D scanners for quality control, we show that our method can be efficiently used for Nominal/Actual comparison. For this scenario, the proposed algorithm significantly outperforms the current state of the art, with regards to registration time and success rate.