Creating Endless Water Flow Animation using Particle Data

Masanori Sotozaki, Yoshinori Dobashi, Tsuyoshi Yamamoto

2016

Abstract

In this paper, we propose an efficient method for synthesizing water animation such as waterfall or rivers using particle-based simulation. Recently, physically based simulation has become a popular technique to create realistic animation of natural phenomena in many applications, e.g. commercial films, movies and games. Particularly, there is a growing demand on synthesizing realistic animation of fluids, such as water. However, realistic fluid animation requires a high computational cost. Some applications requiring real time performances, such as games, cannot afford such a high computational cost. In this paper, we propose an efficient method for creating endless animations of water flow using particle data generated by fluid simulation. We store a set of dynamic particles in a database and use them repeatedly to produce endless animations.

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Paper Citation


in Harvard Style

Sotozaki M., Dobashi Y. and Yamamoto T. (2016). Creating Endless Water Flow Animation using Particle Data . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 236-241. DOI: 10.5220/0005746602340239


in Bibtex Style

@conference{grapp16,
author={Masanori Sotozaki and Yoshinori Dobashi and Tsuyoshi Yamamoto},
title={Creating Endless Water Flow Animation using Particle Data},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016)},
year={2016},
pages={236-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005746602340239},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2016)
TI - Creating Endless Water Flow Animation using Particle Data
SN - 978-989-758-175-5
AU - Sotozaki M.
AU - Dobashi Y.
AU - Yamamoto T.
PY - 2016
SP - 236
EP - 241
DO - 10.5220/0005746602340239