A Markovian-based Approach for Daily Living Activities Recognition

Zaineb Liouane, Tayeb Lemlouma, Philippe Roose, Fréderic Weis, Hassani Messaoud

Abstract

Recognizing activities of daily living plays an important role in healthcare. It is necessary to use an adapted model to simulate the human behavior in a domestic space to monitor the patient harmonically and to intervene in the necessary time. In this paper we tackle this problem using the hierarchical hidden Markov model for representing and recognizing complex indoor activities, we propose a new grammar “Home By Room Activities language” to facilitate the complexity of human scenarios and hold us account to the abnormal activities.

References

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Paper Citation


in Harvard Style

Liouane Z., Lemlouma T., Roose P., Weis F. and Messaoud H. (2016). A Markovian-based Approach for Daily Living Activities Recognition . In Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-169-4, pages 214-219. DOI: 10.5220/0005809502140219


in Bibtex Style

@conference{sensornets16,
author={Zaineb Liouane and Tayeb Lemlouma and Philippe Roose and Fréderic Weis and Hassani Messaoud},
title={A Markovian-based Approach for Daily Living Activities Recognition},
booktitle={Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS,},
year={2016},
pages={214-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005809502140219},
isbn={978-989-758-169-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Confererence on Sensor Networks - Volume 1: SENSORNETS,
TI - A Markovian-based Approach for Daily Living Activities Recognition
SN - 978-989-758-169-4
AU - Liouane Z.
AU - Lemlouma T.
AU - Roose P.
AU - Weis F.
AU - Messaoud H.
PY - 2016
SP - 214
EP - 219
DO - 10.5220/0005809502140219