Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems
Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies,where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efﬁciently. To evaluate the approach, a syntheticdatasetgeneratedfollowingtheproposedmethodologyiscomparedtoarealdataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than signiﬁcant.
Open Access article
Citation : Azkune, G. et al. (2015) Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems. Sensors, 15 (4), pp. 8192-8213
ISSN : 1424-8220
Research Institute : Cyber Technology Institute (CTI)
Peer Reviewed : Yes