A Markovian-based Approach for Daily Living Activities Recognition

Zaineb Liouane 1 Tayeb Lemlouma 2, * Philippe Roose 3 Frédéric Weis 4 Messaoud Hassani 1
* Auteur correspondant
3 T2I
LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour
4 TACOMA - TAngible COMputing Architectures
Inria Rennes – Bretagne Atlantique , IRISA-D2 - RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES
Abstract : Recognizing the 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, called “Home By Room Activities Language”, to facilitate the complexity of human scenarios and consider the abnormal activities.
Type de document :
Communication dans un congrès
The International Conference on Sensor Networks (SENSORNETS'16), Feb 2016, rome, Italy. Proceedings of theInternational Conference on Sensor Networks (SENSORNETS 2016), 2016
Liste complète des métadonnées

https://hal.inria.fr/hal-01280001
Contributeur : Tayeb Lemlouma <>
Soumis le : mardi 8 mars 2016 - 19:59:38
Dernière modification le : mercredi 29 novembre 2017 - 15:41:45
Document(s) archivé(s) le : dimanche 13 novembre 2016 - 11:49:12

Fichier

SensorNetsFinalCR49 (1).pdf
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

  • HAL Id : hal-01280001, version 1
  • ARXIV : 1603.03251

Citation

Zaineb Liouane, Tayeb Lemlouma, Philippe Roose, Frédéric Weis, Messaoud Hassani. A Markovian-based Approach for Daily Living Activities Recognition . The International Conference on Sensor Networks (SENSORNETS'16), Feb 2016, rome, Italy. Proceedings of theInternational Conference on Sensor Networks (SENSORNETS 2016), 2016. 〈hal-01280001〉

Partager

Métriques

Consultations de la notice

345

Téléchargements de fichiers

98