Affiliations: [a] School of Architecture, Computing and Engineering, University of East London, London, UK | [b] School of Computing and Digital Technology, Birmingham City University, Birmingham, UK
Correspondence:
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Corresponding author: Isibor Kennedy Ihianle, School of Architecture, Computing and Engineering, University of East London, London, UK. E-mail: u1051232@uel.ac.uk.
Abstract: To provide assistance and support to the elderly disabled and cognitively impaired, the recognition of their activities of daily living (ADL) must be accurate and precise with regards to the object use for the activity situations. Current knowledge-driven and ontology-based activity recognition techniques model object concepts from assumptions and common everyday knowledge of object use of routine activities. Modelling activities from assumptions and common everyday knowledge of object use could lead to faulty recognition of particular routine activities and possibly undermine abnormal activity trends. A significant step in the recognition of activities of daily living is the discovery of the object use for specific routine activities due to its ability to relate object use to their associated activities. The discovering particular object(s) which are used to perform routine activities could help enhance knowledge-driven ontology-based activity recognition with the object use for specific activities and the associated activities as ontology concepts. This paper focuses on the recognition of simple activities of daily living from object use and interactions in the home environment. We take advantage of the object use for routine activities discovered from a topic model process to augment activity ontology concepts for activity recognition. The experimental results obtained using the Kasteren and Ordonez datasets show it is significantly encouraging, comparable and improved on results published using the same datasets.
