A Markovian-based Approach for Daily Living Activities Recognition
Human-Computer Interaction
2016-03-11 v1 Artificial Intelligence
Computers and Society
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.
Keywords
Cite
@article{arxiv.1603.03251,
title = {A Markovian-based Approach for Daily Living Activities Recognition},
author = {Zaineb Liouane and Tayeb Lemlouma and Philippe Roose and Frédéric Weis and Messaoud Hassani},
journal= {arXiv preprint arXiv:1603.03251},
year = {2016}
}
Comments
The International Conference on Sensor Networks (SENSORNETS'16), Feb 2016, rome, Italy. Proceedings of theInternational Conference on Sensor Networks (SENSORNETS 2016), 2016