Abstract
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.
Highlights
Video cameras are commonly used in video surveillance systems in order to guarantee security in outdoor environments and public places
The performed experimentation shows that the proposed human action recognition approach reaches high recognition rates steadily
This essential part is required in order to both support the desired ambient-assisted living (AAL) services, as well as to enable the privacy-by-context method
Summary
Video cameras are commonly used in video surveillance systems in order to guarantee security in outdoor environments and public places. If vision-based information related to human activity at home were provided, a vast amount of services regarding entertainment, home automation, security and safety, among others, could be deployed, since cameras provide rich sensory information. In AAL, ambient intelligence is applied to the promotion and extension of independent life at home for elderly or impaired people. In this sense, AAL can give diverse types of support to ensure people’s health and safety, and to increase their autonomy and well-being, by means of providing services from the automatic supervision of medication to intelligent monitoring
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