NDLI: Interaction models for multiple-resident activity recognition in a smart home

Content Provider	IEEE Xplore Digital Library
Author	Yi-Ting Chiang Kuo-Chung Hsu Ching-Hu Lu Li-Chen Fu Hsu, J.Y.-J.
Copyright Year	2010
Description	Author affiliation: Department of Computer Science & Information Engineering and The Graduate Institute of Networking and Multimedia, National Taiwan University, R.O.C (Hsu, J.Y.-J.) \|\| Dept. of Computer Science & Information Eng. and Dept. of Electrical Eng., National Taiwan University, R.O.C (Li-Chen Fu) \|\| Dept. of Computer Science & Information Eng., National Taiwan University, R.O.C (Yi-Ting Chiang; Kuo-Chung Hsu; Ching-Hu Lu)
Abstract	Multi-resident activity recognition is among a key enabler in many context-aware applications in a smart home. However, most of prior researches ignore the potential interactions among residents in order to simplify problem complexity. On the other hand, multiple-resident activities are usually recognized using cameras or wearable sensors. However, due to human-centric concerns, it is more preferable to avoid using obtrusive sensors. In this paper, we propose dynamic Bayesian networks which extend coupled hidden Markov models (CHMMs) by adding some vertices to model both individual and cooperative activities. In order to improve performance of the model, we categorize sensor observations based on data association and some domain knowledge to model multiple-resident activity patterns. We then validate the performance using a multi-resident dataset from WSU (Washington State University), which only includes non-obtrusive sensors. The experimental result shows that our model performs better than other baseline classifiers.
Starting Page	3753
Ending Page	3758
File Size	1010566
Page Count	6
File Format	PDF
ISBN	9781424466740
ISSN	21530866
e-ISBN	9781424466764
DOI	10.1109/IROS.2010.5650340
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Humans Intelligent sensors Feature extraction Smart homes Bayesian methods
Content Type	Text
Resource Type	Article

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