loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Sebastian Bullinger ; Christoph Bodensteiner and Michael Arens

Affiliation: Department of Object Recognition, Fraunhofer IOSB, Ettlingen, Germany

Keyword(s): Image-based Modeling, Camera Tracking, Photogrammetry, Structure from Motion, Multi-view Stereo, Blender.

Abstract: We propose a framework that extends Blender to exploit Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques for image-based modeling tasks such as sculpting or camera and motion tracking. Applying SfM allows us to determine camera motions without manually defining feature tracks or calibrating the cameras used to capture the image data. With MVS we are able to automatically compute dense scene models, which is not feasible with the built-in tools of Blender. Currently, our framework supports several state-of-the-art SfM and MVS pipelines. The modular system design enables us to integrate further approaches without additional effort. The framework is publicly available as an open source software package.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.119.141.115

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Bullinger, S.; Bodensteiner, C. and Arens, M. (2021). A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - GRAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 106-112. DOI: 10.5220/0010319801060112

@conference{grapp21,
author={Sebastian Bullinger. and Christoph Bodensteiner. and Michael Arens.},
title={A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - GRAPP},
year={2021},
pages={106-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010319801060112},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - GRAPP
TI - A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking
SN - 978-989-758-488-6
IS - 2184-4321
AU - Bullinger, S.
AU - Bodensteiner, C.
AU - Arens, M.
PY - 2021
SP - 106
EP - 112
DO - 10.5220/0010319801060112
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic