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User recognition in AAL environments

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Detalhes bibliográficos
Resumo:Healthcare projects that intend to decrease the economical and social costs of the real ageing population phenomenon, through the de-localisation of healthcare services delivery and management to the home, have been arising in the scientific community. The VirtualECare project is one of those, so called, Ambient Assisted Living environments, which we have taken a step forward with the introduction of proactive techniques for better adapting to its users, namely elderly or chronic patients, once it is able to learn with their interaction based in contexts. This learning, however, causes the system need to know with whom it is interacting. Basic detection techniques based in possible devices that users carries along with them (e.g. RFID tags, mobile phones, ...) are not good enough, since they can lose/forgot/switch them. To obtain the expected results the technology used has to be more advanced and available in several platforms. One possible and already fairly developed technique is Facial Recognition, and it appears to be the most appropriate one to handle the problem.This document exposes the initial approach of the VirtualECare project to the Facial Recognition area.
Autores principais:Costa, Ricardo
Outros Autores:Novais, Paulo; Costa, Ângelo; Lima, Luís; Neves, José
Assunto:Ambient Assisted Living e-Health Face recognition
Ano:2010
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Healthcare projects that intend to decrease the economical and social costs of the real ageing population phenomenon, through the de-localisation of healthcare services delivery and management to the home, have been arising in the scientific community. The VirtualECare project is one of those, so called, Ambient Assisted Living environments, which we have taken a step forward with the introduction of proactive techniques for better adapting to its users, namely elderly or chronic patients, once it is able to learn with their interaction based in contexts. This learning, however, causes the system need to know with whom it is interacting. Basic detection techniques based in possible devices that users carries along with them (e.g. RFID tags, mobile phones, ...) are not good enough, since they can lose/forgot/switch them. To obtain the expected results the technology used has to be more advanced and available in several platforms. One possible and already fairly developed technique is Facial Recognition, and it appears to be the most appropriate one to handle the problem.This document exposes the initial approach of the VirtualECare project to the Facial Recognition area.