Sensor-Based Human Activity Recognition in a Multi-user Scenario

Authors:
Liang Wang;Tao Gu;Xianping Tao;Jian Lu
Affiliations:
State Key Laboratory for Novel Software Technology, Nanjing University,;Department of Mathematics and Computer Science, University of Southern Denmark,;State Key Laboratory for Novel Software Technology, Nanjing University,;State Key Laboratory for Novel Software Technology, Nanjing University,
Venue:
AmI '09 Proceedings of the European Conference on Ambient Intelligence
Year:
2009

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Abstract

Existing work on sensor-based activity recognition focuses mainly on single-user activities. However, in real life, activities are often performed by multiple users involving interactions between them. In this paper, we propose Coupled Hidden Markov Models (CHMMs) to recognize multi-user activities from sensor readings in a smart home environment. We develop a multimodal sensing platform and present a theoretical framework to recognize both single-user and multi-user activities. We conduct our trace collection done in a smart home, and evaluate our framework through experimental studies. Our experimental result shows that we achieve an average accuracy of 85.46% with CHMMs.