Bootstrapping Vector Fields

Paula Ceccon Ribeiro, Hélio Lopes

2019

Abstract

Vector fields play an essential role in a large range of scientific applications. They are commonly generated through computer simulations. Such simulations may be a costly process since they usually require high computational time. When researchers want to quantify the uncertainty in such kind of applications, usually an ensemble of vector fields realizations are generated, making the process much more expensive. In this work, we propose the use of the Bootstrap technique jointly with the Helmholtz-Hodge Decomposition as a tool for stochastic generation of vector fields. Results show that this technique is capable of generating a variety of realizations that can be used to quantify the uncertainty in applications that use vector fields as an input.

Paper Citation

in Harvard Style

Ribeiro P. and Lopes H. (2019). Bootstrapping Vector Fields. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP; ISBN 978-989-758-354-4, SciTePress, pages 19-30. DOI: 10.5220/0007248900190030

in Bibtex Style

@conference{grapp19,
author={Paula Ceccon Ribeiro and Hélio Lopes},
title={Bootstrapping Vector Fields},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP},
year={2019},
pages={19-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007248900190030},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP
TI - Bootstrapping Vector Fields
SN - 978-989-758-354-4
AU - Ribeiro P.
AU - Lopes H.
PY - 2019
SP - 19
EP - 30
DO - 10.5220/0007248900190030
PB - SciTePress