Combining Users’ Activity Survey and Simulators to Evaluate Human Activity Recognition Systems
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DeustoTech—Deusto Institute of Technology, University of Deusto, Avda Universidades 24, Bilbao 48007, Spain
2
School of Computer Science and Informatics, De Montfort University, Leicester, LE19BH, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Jesús Fontecha
Sensors 2015, 15(4), 8192-8213; https://doi.org/10.3390/s150408192
Received: 25 February 2015 / Revised: 24 March 2015 / Accepted: 27 March 2015 / Published: 8 April 2015
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 synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant.
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Keywords:
evaluation methodology; activity recognition; synthetic dataset generator; activity survey
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Azkune, G.; Almeida, A.; López-de-Ipiña, D.; Chen, L. Combining Users’ Activity Survey and Simulators to Evaluate Human Activity Recognition Systems. Sensors 2015, 15, 8192-8213.
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