Next Article in Journal
Multi-Model Estimation Based Moving Object Detection for Aerial Video
Next Article in Special Issue
A Novel Software Architecture for the Provision of Context-Aware Semantic Transport Information
Previous Article in Journal
Motion-Blurred Particle Image Restoration for On-Line Wear Monitoring
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(4), 8192-8213; doi:10.3390/s150408192

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

1
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
Received: 25 February 2015 / Revised: 24 March 2015 / Accepted: 27 March 2015 / Published: 8 April 2015
View Full-Text   |   Download PDF [370 KB, uploaded 8 April 2015]   |  

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 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. View Full-Text
Keywords: evaluation methodology; activity recognition; synthetic dataset generator; activity survey 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. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top