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Authors: Negar Ghourchian and Doina Precup

Affiliation: McGill University, Canada

Keyword(s): Activity Recognition, Sensor Selection, Active Learning.

Related Ontology Subjects/Areas/Topics: Active Learning ; Applications ; Classification ; Learning of Action Patterns ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: Activity recognition is a key component of human-machine interaction applications. Information obtained from sensors in smart wearable devices is especially valuable, because these devices have become ubiquitous, and they record large amounts of data. Machine learning algorithms can then be used to process this data. However, wearable devices impose restrictions in terms of computation and energy resources, which need to be taken into account by a learning algorithm. We propose to use a real-time learning approach, which interactively determines the most effective set of modalities (or features) for classification, given the task at hand. Our algorithm optimizes sensor selection, in order to consume less power, while still maintaining good accuracy in classifying sequences of activities. Performance on a large, noisy dataset including four different sensing modalities shows that this is a promising approach.

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Paper citation in several formats:
Ghourchian, N. and Precup, D. (2013). Smart Classifier Selection for Activity Recognition on Wearable Devices. In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-8565-41-9; ISSN 2184-4313, SciTePress, pages 581-585. DOI: 10.5220/0004269805810585

@conference{icpram13,
author={Negar Ghourchian. and Doina Precup.},
title={Smart Classifier Selection for Activity Recognition on Wearable Devices},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2013},
pages={581-585},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004269805810585},
isbn={978-989-8565-41-9},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Smart Classifier Selection for Activity Recognition on Wearable Devices
SN - 978-989-8565-41-9
IS - 2184-4313
AU - Ghourchian, N.
AU - Precup, D.
PY - 2013
SP - 581
EP - 585
DO - 10.5220/0004269805810585
PB - SciTePress