A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking

Sebastian Bullinger, Christoph Bodensteiner, Michael Arens

2021

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.

Paper Citation

in Harvard Style

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) - Volume 1: GRAPP; ISBN 978-989-758-488-6, SciTePress, pages 106-112. DOI: 10.5220/0010319801060112

in Bibtex Style

@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) - Volume 1: GRAPP},
year={2021},
pages={106-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010319801060112},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 1: GRAPP
TI - A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking
SN - 978-989-758-488-6
AU - Bullinger S.
AU - Bodensteiner C.
AU - Arens M.
PY - 2021
SP - 106
EP - 112
DO - 10.5220/0010319801060112
PB - SciTePress