Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems

Date

2015-04-08

Advisors

Journal Title

Journal ISSN

ISSN

1424-8220

Volume Title

Publisher

Sensors

Type

Article

Peer reviewed

Yes

Abstract

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.

Description

Open Access article

Keywords

evaluation methodology, activity recognition, synthetic dataset generator, activity survey

Citation

Azkune, G. et al. (2015) Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems. Sensors, 15 (4), pp. 8192-8213

Rights

Research Institute

Cyber Technology Institute (CTI)