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A topological approach for human movement classification and anticipation

Communication avec acte
Author
BENSEKKA, Chakib Arslane
495876 Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] [Le2i]
GUILLET, Christophe
495876 Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] [Le2i]
MERIENNE, Frédéric
495876 Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] [Le2i]
POZZO, Thierry
178678 Cognition, Action, et Plasticité Sensorimotrice [Dijon - U1093] [CAPS]

URI
http://hdl.handle.net/10985/12777
DOI
10.1016/j.gaitpost.2017.06.387
Date
2017

Abstract

The motion capture systems are increasingly used for biomedical purposes. In order to recognize and classify the movements, however whole-body movements using passive markers, generate a huge amount of data. Can topological data analysis methods improve the recognition of movements? Can we use the results of this analysis combined with particular types of neural networks to anticipate the continuation of a movement?

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