Eugene Ch'ng
The development of a collaborative virtual environment for 3D reconstruction of cuneiform tablets
Ch'ng, Eugene; Woolley, Sandra I.; Hernandez-Munoz, Luis; Collins, Tim; Lewis, Andrew; Gehlken, Erlend
Authors
Dr Sandra Woolley s.i.woolley@keele.ac.uk
Luis Hernandez-Munoz
Tim Collins
Andrew Lewis
Erlend Gehlken
Contributors
E. Ch'Ng
Other
S.I. Woolley
Other
L. Hernandez-Munoz
Other
T. Collins
Other
A. Lewis
Other
E. Gehlken
Other
Abstract
The efficient reconstruction of ancient cuneiform tablets has been a challenging problem over many decades, which if an approach is found to speed up the rate of potential fragment joins, will lead to a discovery of rich historical records of knowledge inscribed 5,000 years ago. This paper describes The Leverhulme Trust funded development of a crowd-sourcing collaborative virtual environment via the identification of cooperative personalities. We conducted experiments in which 12 groups of 3 participants collaborated to reconstruct fragments in a laboratory 3D puzzle virtual environment. Personality types were analysed together with NASA TLX workloads and task performance. We discovered that patterns exist for each of the virtual interaction modalities, demonstrating a potential for profiling systems to group personality types for maximising the effective reconstruction of cuneiform fragments.
Citation
Ch'ng, E., Woolley, S. I., Hernandez-Munoz, L., Collins, T., Lewis, A., & Gehlken, E. (2014, December). The development of a collaborative virtual environment for 3D reconstruction of cuneiform tablets. Presented at 2014 International Conference on Virtual Systems & Multimedia (VSMM), Hong Kong, China
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2014 International Conference on Virtual Systems & Multimedia (VSMM) |
Start Date | Dec 9, 2014 |
End Date | Dec 12, 2014 |
Online Publication Date | Jun 29, 2015 |
Publication Date | 2014 |
Deposit Date | Nov 9, 2023 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
DOI | https://doi.org/10.1109/VSMM.2014.7136692 |
Public URL | https://keele-repository.worktribe.com/output/622967 |
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