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Authors: Rogério E. da Silva 1 ; Jan Ondřej 2 and Aljosa Smolic 3

Affiliations: 1 V-SENSE, School of Computer Science and Statistics, Trinity College Dublin, Ireland, Department of Computer Science, Santa Catarina State University, Brazil ; 2 V-SENSE, School of Computer Science and Statistics, Trinity College Dublin, Ireland, Volograms, Dublin, Ireland ; 3 V-SENSE, School of Computer Science and Statistics, Trinity College Dublin, Ireland

ISBN: 978-989-758-354-4

Keyword(s): Human Motion Classification, Motion Capture, Content Analysis, Deep Learning, Artificial Intelligence.

Abstract: Creative studios tend to produce an overwhelming amount of content everyday and being able to manage these data and reuse it in new productions represent a way for reducing costs and increasing productivity and profit. This work is part of a project aiming to develop reusable assets in creative productions. This paper describes our first attempt using deep learning to classify human motion from motion capture files. It relies on a long short-term memory network (LSTM) trained to recognize action on a simplified ontology of basic actions like walking, running or jumping. Our solution was able of recognizing several actions with an accuracy over 95% in the best cases.

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Paper citation in several formats:
E. da Silva, R.; Ondřej, J. and Smolic, A. (2019). Using LSTM for Automatic Classification of Human Motion Capture Data.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, ISBN 978-989-758-354-4, pages 236-243. DOI: 10.5220/0007349902360243

@conference{grapp19,
author={Rogério E. da Silva. and Jan Ond\v{r}ej. and Aljosa Smolic.},
title={Using LSTM for Automatic Classification of Human Motion Capture Data},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,},
year={2019},
pages={236-243},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007349902360243},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,
TI - Using LSTM for Automatic Classification of Human Motion Capture Data
SN - 978-989-758-354-4
AU - E. da Silva, R.
AU - Ondřej, J.
AU - Smolic, A.
PY - 2019
SP - 236
EP - 243
DO - 10.5220/0007349902360243

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