Transferring knowledge of activity recognition across sensor networks

Authors:
T. L. M. van Kasteren;G. Englebienne;B. J. A. Kröse
Affiliations:
Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, The Netherlands;Intelligent Systems Lab Amsterdam, University of Amsterdam, Amsterdam, The Netherlands
Venue:
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
Year:
2010

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Abstract

A problem in performing activity recognition on a large scale (i.e. in many homes) is that a labelled data set needs to be recorded for each house activity recognition is performed in. This is because most models for activity recognition require labelled data to learn their parameters. In this paper we introduce a transfer learning method for activity recognition which allows the use of existing labelled data sets of various homes to learn the parameters of a model applied in a new home. We evaluate our method using three large real world data sets and show our approach achieves good classification performance in a home for which little or no labelled data is available.