We present SfM Flow, a Blender add-on that provides a toolset for the evaluation of three-dimensional reconstructions obtained form images. 3D reconstruction is increasingly becoming popular and, to date, many techniques are available to perform it. Choosing which technology to use for a specific 3D reconstruction task can be resource and time-consuming. By using this tool it is possible to create images of a virtual 3D scene, perform 3D reconstructions starting from the generated images using Structure from Motion pipelines, and evaluate the accuracy of the obtained 3D reconstruction. The evaluation is carried out comparing the 3D reconstruction with the virtual scene's geometry, that constitutes an exact ground truth, without the need for complex setup and dedicated hardware for the acquisition of a real scene. Furthermore, SfM Flow includes support for different lighting, depth of field, and motion blur setups, thus allowing to stress the 3D reconstruction pipelines under common critical conditions.

Marelli, D., Bianco, S., Ciocca, G. (2022). SfM Flow: A comprehensive toolset for the evaluation of 3D reconstruction pipelines. SOFTWAREX, 17(January 2022) [10.1016/j.softx.2021.100931].

SfM Flow: A comprehensive toolset for the evaluation of 3D reconstruction pipelines

Marelli, D
Primo
;
Bianco, S
Secondo
;
Ciocca, G
Ultimo
2022

Abstract

We present SfM Flow, a Blender add-on that provides a toolset for the evaluation of three-dimensional reconstructions obtained form images. 3D reconstruction is increasingly becoming popular and, to date, many techniques are available to perform it. Choosing which technology to use for a specific 3D reconstruction task can be resource and time-consuming. By using this tool it is possible to create images of a virtual 3D scene, perform 3D reconstructions starting from the generated images using Structure from Motion pipelines, and evaluate the accuracy of the obtained 3D reconstruction. The evaluation is carried out comparing the 3D reconstruction with the virtual scene's geometry, that constitutes an exact ground truth, without the need for complex setup and dedicated hardware for the acquisition of a real scene. Furthermore, SfM Flow includes support for different lighting, depth of field, and motion blur setups, thus allowing to stress the 3D reconstruction pipelines under common critical conditions.
Articolo in rivista - Articolo scientifico
3D reconstruction evaluation; Blender add-on; Structure from Motion (SfM); Synthetic data generation;
English
Marelli, D., Bianco, S., Ciocca, G. (2022). SfM Flow: A comprehensive toolset for the evaluation of 3D reconstruction pipelines. SOFTWAREX, 17(January 2022) [10.1016/j.softx.2021.100931].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/341970
Citazioni
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
Social impact