Description

This work studies the quality of probabilistic model registration using feature-matching techniques based on the the FPFH and the SHOT descriptors. Furthermore, the quality of the underlying geometry, and therefore the effectiveness of the descriptors for matching purposes, is affected by variations in the conditions of the data collection. A major contribution of this work is to evaluate the quality of feature-based registration of PVM models under different scenarios that reflect the kind of variability observed across collections from different times instances. More precisely, this work investigates variability in terms of model discretization, resolution and sampling density, errors in the camera orientation, and changes illumination and geographic characteristics.  A corresponding manuscript is under preparation.