Zhou, Jiang 
ORCID: 0000-0002-3067-8512, Duane, Aaron ORCID: 0000-0002-9825-1654, Albatal, Rami ORCID: 0000-0002-9269-8578, Gurrin, Cathal ORCID: 0000-0003-2903-3968 and Johansen, Dag
(2015)
Wearable cameras for real-time activity annotation.
In: 21st International Conference on Multimedia Modelling (MMM2015), 5-7 Jan 2015, Sydney, Australia.
ISBN 978-3-319-14442-9
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Abstract
Google Glass has potential to be a real-time data capture and annotation tool. With professional sports as a use-case, we present a platform which helps a football coach capture and annotate interesting events using Google Glass. In our implementation, an interesting event is indicated by a predefined hand gesture or motion, and our platform can automatically detect these gestures in a video without training any classifier. Three event detectors are examined and our experiment shows that the detector with combined edgeness and color moment features gives the best detection performance.
| Item Type: | Conference or Workshop Item (Other) |
|---|---|
| Event Type: | Conference |
| Refereed: | Yes |
| Uncontrolled Keywords: | Annotation; Google glass |
| Subjects: | Computer Science > Lifelog |
| DCU Faculties and Centres: | Research Initiatives and Centres > INSIGHT Centre for Data Analytics |
| Published in: | MMM 2015. Lecture Notes in Computer Science 8936. Springer. ISBN 978-3-319-14442-9 |
| Publisher: | Springer |
| Official URL: | http://link.springer.com/chapter/10.1007%2F978-3-319-14442-9_38 |
| 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 |
| ID Code: | 20291 |
| Deposited On: | 22 Jan 2015 14:47 by Jiang Zhou . Last Modified 15 Dec 2021 16:25 |
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- Wearable cameras for real-time activity annotation. (deposited 22 Jan 2015 14:47) [Currently Displayed]
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