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2018 | Supplement | Buchkapitel

Human Activities Transfer Learning for Assistive Robotics

verfasst von : David Ada Adama, Ahmad Lotfi, Caroline Langensiepen, Kevin Lee

Erschienen in: Advances in Computational Intelligence Systems

Verlag: Springer International Publishing

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Abstract

Assisted living homes aim to deploy tools to promote better living of elderly population. One of such tools is assistive robotics to perform tasks a human carer would normally be required to perform. For assistive robots to perform activities without explicit programming, a major requirement is learning and classifying activities while it observes a human carry out the activities. This work proposes a human activity learning and classification system from features obtained using 3D RGB-D data. Different classifiers are explored in this approach and the system is evaluated on a publicly available data set, showing promising results which is capable of improving assistive robots performance in living environments.

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Metadaten
Titel
Human Activities Transfer Learning for Assistive Robotics
verfasst von
David Ada Adama
Ahmad Lotfi
Caroline Langensiepen
Kevin Lee
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-66939-7_22