A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context
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Título: | A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context |
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Autor/es: | Chaaraoui, Alexandros Andre | Padilla López, José Ramón | Ferrandez-Pastor, Francisco-Javier | Nieto-Hidalgo, Mario | Flórez-Revuelta, Francisco |
Grupo/s de investigación o GITE: | Informática Industrial y Redes de Computadores | Domótica y Ambientes Inteligentes |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Palabras clave: | Intelligent monitoring | Vision system | Ambient-assisted living | Human behaviour analysis | Human action recognition | Multi-view recognition | Telecare monitoring | Privacy preservation | Privacy by context |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores |
Fecha de publicación: | 20-may-2014 |
Editor: | MDPI |
Cita bibliográfica: | Chaaraoui AA, Padilla-López JR, Ferrández-Pastor FJ, Nieto-Hidalgo M, Flórez-Revuelta F. A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context. Sensors. 2014; 14(5):8895-8925. doi:10.3390/s140508895 |
Resumen: | Due to progress and demographic change, society is facing a crucial challenge related to increased life expectancy and a higher number of people in situations of dependency. As a consequence, there exists a significant demand for support systems for personal autonomy. This article outlines the vision@home project, whose goal is to extend independent living at home for elderly and impaired people, providing care and safety services by means of vision-based monitoring. Different kinds of ambient-assisted living services are supported, from the detection of home accidents, to telecare services. In this contribution, the specification of the system is presented, and novel contributions are made regarding human behaviour analysis and privacy protection. By means of a multi-view setup of cameras, people’s behaviour is recognised based on human action recognition. For this purpose, a weighted feature fusion scheme is proposed to learn from multiple views. In order to protect the right to privacy of the inhabitants when a remote connection occurs, a privacy-by-context method is proposed. The experimental results of the behaviour recognition method show an outstanding performance, as well as support for multi-view scenarios and real-time execution, which are required in order to provide the proposed services. |
Patrocinador/es: | This work has been partially supported by the Spanish Ministry of Science and Innovation under project ‘Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar’ (TIN2010-20510-C04-02). Alexandros Andre Chaaraoui and José Ramón Padilla-López acknowledge financial support by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana (fellowships ACIF/2011/160 and ACIF/2012/064, respectively). |
URI: | http://hdl.handle.net/10045/37208 |
ISSN: | 1424-8220 |
DOI: | 10.3390/s140508895 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/) |
Revisión científica: | si |
Versión del editor: | http://dx.doi.org/10.3390/s140508895 |
Aparece en las colecciones: | INV - DAI - Artículos de Revistas INV - AmI4AHA - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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2014_Chaaraoui_etal_Sensors.pdf | 2,84 MB | Adobe PDF | Abrir Vista previa | |
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