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Authors: Sebastian Silva ; Sergio Sugahara and Willy Ugarte

Affiliation: Universidad Peruana de Ciencias Aplicadas (UPC), Lima, Peru

Keyword(s): Neural Networks, Locomotion, Human Motion, Character Animation, Character Control, Deep Learning.

Abstract: The increasing need for more realistic animations has resulted in the implementation of various systems that try to overcome this issue by controlling the character at a base level based on complex techniques. In our work we are using a Phase Functioned Neural Network for generating the next pose of the character in real time while making a comparison with a modified version of the model. The current basic model lacks the ability of producing reactive animations with objects of their surrounding but only reacts to the terrain the character is standing on. Therefore, adding a layer of Rigs with Inverse Kinematics and Blending Trees will allow us to switch between actions depending on the object and adjust the character to fit properly. Our results showed that our proposal improves significantly previous results and that inverse kinematics is essential for this improvement.

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Paper citation in several formats:
Silva, S.; Sugahara, S. and Ugarte, W. (2022). Neuranimation: Reactive Character Animations with Deep Neural Networks. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - GRAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 252-259. DOI: 10.5220/0010896500003124

@conference{grapp22,
author={Sebastian Silva. and Sergio Sugahara. and Willy Ugarte.},
title={Neuranimation: Reactive Character Animations with Deep Neural Networks},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - GRAPP},
year={2022},
pages={252-259},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010896500003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - GRAPP
TI - Neuranimation: Reactive Character Animations with Deep Neural Networks
SN - 978-989-758-555-5
IS - 2184-4321
AU - Silva, S.
AU - Sugahara, S.
AU - Ugarte, W.
PY - 2022
SP - 252
EP - 259
DO - 10.5220/0010896500003124
PB - SciTePress

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