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QEST
2015
IEEE

A Continuous-Time Model-Based Approach to Activity Recognition for Ambient Assisted Living

7 years 11 months ago
A Continuous-Time Model-Based Approach to Activity Recognition for Ambient Assisted Living
In Ambient Assisted Living (AAL), Activity Recognition (AR) plays a crucial role in filling the semantic gap between sensor data and interpretation needed at the application level. We propose a quantitative model-based approach to on-line prediction of activities that takes into account not only the sequencing of events but also the continuous duration of their inter-occurrence times: given a stream of time-stamped and typed events, online transient analysis of a continuous-time stochastic model is used to derive a measure of likelihood for the currently performed activity and to predict its evolution until the next event; while the structure of the model is predefined, its actual topology and stochastic parameters are automatically derived from the statistics of observed events. The approach is validated with reference to a public data set widely used in applications of AAL, providing results that show comparable performance with state-of-the-art offline approaches, namely Hidden Ma...
Laura Carnevali, Christopher Nugent, Fulvio Patara
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where QEST
Authors Laura Carnevali, Christopher Nugent, Fulvio Patara, Enrico Vicario
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