Activity recognition using incremental learning
College
College of Computer Studies
Department/Unit
Software Technology
Document Type
Conference Proceeding
Source Title
Proceedings of the 6th IASTED International Conference on Human-Computer Interaction, HCI 2011
First Page
105
Last Page
111
Publication Date
9-2-2011
Abstract
This paper presents an unsupervised incremental learning approach for activity recognition. Activity recognition is important because ambient intelligent spaces need to recognize the activity of the inhabitant before it can provide the appropriate support or assistance. However, building a knowledgebase of appropriate support is difficult, tedious and expensive. It is not guaranteed to be complete, therefore, it is unable to handle novel situations. In this paper an unsupervised incremental algorithm was used on an 82-hour activity corpus of daily living was gathered by having a male inhabitant occupy the living space for three to four hours at a time. Accuracy is 93.04%.
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Digitial Object Identifier (DOI)
10.2316/P.2011.747-035
Recommended Citation
Trogo-Oblena, R. S., Suarez, M., Bautista, N., Cua, M., Gonzales, J., & Urquiola, M. B. (2011). Activity recognition using incremental learning. Proceedings of the 6th IASTED International Conference on Human-Computer Interaction, HCI 2011, 105-111. https://doi.org/10.2316/P.2011.747-035
Disciplines
Computer Sciences | Software Engineering
Keywords
Human activity recognition; Ubiquitous computing
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