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Fast human activity recognition in lifelogging

Terziyski, Stefan, Albatal, Rami ORCID: 0000-0002-9269-8578 and Gurrin, Cathal ORCID: 0000-0003-2903-3968 (2015) Fast human activity recognition in lifelogging. MultiMedia Modeling, 8936 . pp. 369-379. ISSN 0302-9743

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Abstract

This paper addresses the problem of fast Human Activity Recognition (HAR) in visual lifelogging. We identify the importance of visual features related to HAR and we specifically evaluate the HAR discrimination potential of Colour Histograms and Histogram of Oriented Gradients. In our evaluation we show that colour can be a low-cost and effective means of low-cost HAR when performing single-user classification. It is also noted that, while much more efficient, global image descriptors perform as well or better than local descriptors in our HAR experiments. We believe that both of these findings are due to the fact that a user’s lifelog is rich in reoccurring scenes and environments.

Item Type:Article (Published)
Refereed:Yes
Additional Information:This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under grant number SFI/12/RC/2289.
Subjects:Computer Science > Lifelog
Computer Science > Multimedia systems
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Publisher:Springer International Publishing
Official URL:http://dx.doi.org/10.1007/978-3-319-14442-9
Copyright Information:© 2015 Springer The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:20441
Deposited On:11 Feb 2015 09:55 by Stefan Terziyski . Last Modified 15 Dec 2021 16:24

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