Multimodal detection of human interaction events in a nursing home environment

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Multimodal detection of human interaction events in a nursing home environment

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International Conference on Multimodal Interfaces archive
Proceedings of the 6th international conference on Multimodal interfaces table of contents

State College, PA, USA

SESSION: Multimodal applications table of contents

Pages: 82 - 89

Year of Publication: 2004

ISBN:1-58113-995-0

Authors

Datong Chen	Carnegie Mellon University, Pittsburgh, PA
Robert Malkin	Carnegie Mellon University, Pittsburgh, PA
Jie Yang	Carnegie Mellon University, Pittsburgh, PA

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 6, Downloads (12 Months): 35, Citation Count: 1

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ABSTRACT

In this paper, we propose a multimodal system for detecting human activity and interaction patterns in a nursing home. Activities of groups of people are firstly treated as interaction patterns between any pair of partners and are then further broken into individual activities and behavior events using a multi-level context hierarchy graph. The graph is implemented using a dynamic Bayesian network to statistically model the multi-level concepts. We have developed a coarse-to-fine prototype system to illustrate the proposed concept. Experimental results have demonstrated the feasibility of the proposed approaches. The objective of this research is to automatically create concise and comprehensive reports of activities and behaviors of patients to support physicians and caregivers in a nursing facility.

REFERENCES

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