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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

Eugene Ch'ng

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