Arnaud Ahouandjinou ; Eugène C. Ezin ; Cina Motamed - Temporal and Hierarchical HMM for Activity Recognition Applied in Visual Medical Monitoring using a Multi-Camera System

arima:1999 - Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, August 30, 2015, Volume 21 - 2015 - Special issue - CARI 2014 - https://doi.org/10.46298/arima.1999
Temporal and Hierarchical HMM for Activity Recognition Applied in Visual Medical Monitoring using a Multi-Camera System

Authors: Arnaud Ahouandjinou ; Eugène C. Ezin ; Cina Motamed

We address in this paper an improved medical monitoring system through an automatic recognition of human activity in Intensive Care Units (ICUs). A multi camera vision system approach is proposed to collect video sequence for automatic analysis and interpretation of the scene. The latter is performed using Hidden Markov Model (HMM) with explicit state duration combine at the management of the hierarchical structure of the scenario. Significant experiments are carried out on the proposed monitoring system in a hospital's cardiology section in order to prove the need for computer-aided patient supervision to help clinicians in the decision making process. Temporal and hierarchical HMM handles explicitly the state duration and then provides a suitable solution for the automatic recognition of temporal events. Finally, the use of Temporal HMM (THMM) based approach improves the scenario recognition performance compared to the result of standard HMM models.


Volume: Volume 21 - 2015 - Special issue - CARI 2014
Published on: August 30, 2015
Submitted on: February 13, 2015
Keywords: Monitoring System in ICUs, Human Activities Recognition (HAR), Video Analysis and interpretation, Classic HMM and HMMs with explicit state duration.,Système de surveillance en USIs, Reconnaissance d'activités humaines, Analyse et interprétation vidéo, MMC classique et à durée d'état explicite, MMC hiérarchique.,[INFO] Computer Science [cs],[MATH] Mathematics [math]


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