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Human activities transfer learning for assistive robotics
conference contribution
posted on 2018-01-01, 00:00 authored by D A Adama, A Lotfi, C Langensiepen, Kevin LeeKevin LeeAssisted 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.