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A Markovian-based Approach for Daily Living Activities Recognition

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.
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Contributor : Tayeb Lemlouma Connect in order to contact the contributor
Submitted on : Tuesday, March 8, 2016 - 7:59:38 PM
Last modification on : Tuesday, February 15, 2022 - 3:09:51 AM
Long-term archiving on: : Sunday, November 13, 2016 - 11:49:12 AM


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


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. ⟨hal-01280001⟩



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