- Transferring knowledge of activity recognition across sensor networks
- Lecture Notes in Computer Science
- Pages (from-to)
- Document type
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
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.
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- Proceedings title: Pervasive computing: 8th international conference, Pervasive 2010, Helsinki, Finland, May 17-20, 2010:
Place of publication: Berlin
Editors: P. Floréen, A. Krüger, M. Spasojevic
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