On the Use of Quality Metrics to Characterize Structured Light-based Point Cloud Acquisitions

Abstract

Even if 3D acquisition systems are nowadays more and more efficient, the resulting point clouds nevertheless contain quality defects that must be taken into account beforehand, in order to better anticipate and control their effects. Assessing the quality of 3D acquisitions has therefore become a major issue for scan planning. This paper presents several quality metrics that are then studied to identify those that could be used to optimize the acquisition positions to perform an automatic scan. From the experiments, it appears that, when considering multiple acquisition positions, the coverage ratio and score indicator have significant changes and can be used to evaluate the quality of the measurements. Differently, other indicators such as efficacy ratio, registration error and metrological characteristics are insensitive to some acquisition positions