Performance evaluation of a multi-image 3D reconstruction software on a low-feature artefact

Nowadays, multi-image 3D reconstruction is an active research field and a number of commercial and free software tools have been already made available to the public. These provide methods for the 3D reconstruction of real world objects by matching feature points and retrieving depth information from a set of unordered digital images. This is achieved by exploiting computer vision algorithms such as Structure-From-Motion (SFM) and Dense Multi-View 3D Reconstruction (DMVR). In this work, we evaluate the performance of a low-cost commercial SFM–DMVR software by digitising a Cycladic woman figurine. Although the surface properties of the specific artefact are considered 3D laser scanner friendly, its almost featureless white-grey surface composes a challenging digitisation candidate for image based methodologies as no strong feature points are available. We quantify the quality of the 3D data produced by the SFM–DMVR software in relation to the data produced by a high accuracy 3D laser scanner in terms of surface deviation and topological errors. We question the applicability and efficiency of two digitisation pipelines (SFM–DMVR and laser scanner) in relation to hardware requirements, background knowledge and man-hours. This is achieved by producing a complete 3D digital replica of the Cycladic artefact by following both pipelines.