Duane, Aaron and Gurrin, Cathal ORCID: 0000-0003-2903-3968 (2017) Pilot study to investigate feasibility of visual lifelog exploration in virtual reality. In: Lifelogging Tools and Applications LTA'17, 23 Oct 2017, Mountain View, CA, USA. ISBN 978-1-4503-5503-2
Abstract
The prevalence of modern technology has enabled people to record
a digital trove of life experiences and these datasets continue to grow
exponentially day by day. Exploring these huge datasets effectively
has been the subject of much research in the lifelogging community.
In this paper we describe a pilot study performed to investigate
the feasibility of using virtual reality as a platform for exploring
visual lifelog data. The dataset used in this experiment consisted of
image data captured by wearable cameras and keywords describing
the visual content of each image. The results of this experiment
suggested there was no notable reduction in user performance
when using the virtual reality platform, compared to a conventional
desktop environment. This research was performed as part of a
larger study to investigate the overall potential of virtual reality as
a platform for visual lifelog exploration.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Lifelogging; Virtual Reality |
Subjects: | Computer Science > Lifelog |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > INSIGHT Centre for Data Analytics |
Published in: | Gurrin, Cathal, Giró-i-Nieto, Xavier, Radeva, Petia, Joho, Hideo, Dang-Nguyen, Duc-Tien and Dimiccoli, Mariella, (eds.) Proceedings of the 2nd Workshop on Lifelogging Tools and Applications. LTA 2. ACM. ISBN 978-1-4503-5503-2 |
Publisher: | ACM |
Official URL: | https://doi.org/10.1145/3133202.3133208 |
Copyright Information: | © 2017 Association for Computing Machinery. |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Science Foundation Ireland (SFI) under grant number SFI/12/RC/2289. |
ID Code: | 22777 |
Deposited On: | 07 Nov 2018 12:45 by Thomas Murtagh . Last Modified 15 Dec 2021 16:08 |
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