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Audio-visual-olfactory resource allocation for tri-modal virtual environments
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Doukakis, Efstratios, Debattista, Kurt, Bashford-Rogers, Thomas, Dhokia, Amar, Asadipour, Ali, Chalmers, Alan and Harvey, C. (2019) Audio-visual-olfactory resource allocation for tri-modal virtual environments. IEEE Transactions on Visualization and Computer Graphics, 25 (5). pp. 1865-1875. doi:10.1109/TVCG.2019.2898823
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WRAP-audio-visual-olfactory-resource-allocation-tri-modal-virtual-environments-Debattista-2019.pdf - Accepted Version - Requires a PDF viewer. Download (21Mb) | Preview |
Official URL: http://doi.org/10.1109/TVCG.2019.2898823
Abstract
Virtual Environments (VEs) provide the opportunity to simulate a wide range of applications, from training to entertainment, in a safe and controlled manner. For applications which require realistic representations of real world environments, the VEs need to provide multiple, physically accurate sensory stimuli. However, simulating all the senses that comprise the human sensory system (HSS) is a task that requires significant computational resources. Since it is intractable to deliver all senses at the highest quality, we propose a resource distribution scheme in order to achieve an optimal perceptual experience within the given computational budgets. This paper investigates resource balancing for multi-modal scenarios composed of aural, visual and olfactory stimuli. Three experimental studies were conducted. The first experiment identified perceptual boundaries for olfactory computation. In the second experiment, participants (N=25) were asked, across a fixed number of budgets (N=5) , to identify what they perceived to be the best visual, acoustic and olfactory stimulus quality for a given computational budget. Results demonstrate that participants tend to prioritize visual quality compared to other sensory stimuli. However, as the budget size is increased, users prefer a balanced distribution of resources with an increased preference for having smell impulses in the VE. Based on the collected data, a quality prediction model is proposed and its accuracy is validated against previously unused budgets and an untested scenario in a third and final experiment.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||||
| Divisions: | Faculty of Science > Engineering | ||||||||
| Library of Congress Subject Headings (LCSH): | Virtual reality, Computer simulation | ||||||||
| Journal or Publication Title: | IEEE Transactions on Visualization and Computer Graphics | ||||||||
| Publisher: | Institute of Electrical and Electronics Engineers | ||||||||
| ISSN: | 1077-2626 | ||||||||
| Official Date: | May 2019 | ||||||||
| Dates: |
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| Volume: | 25 | ||||||||
| Number: | 5 | ||||||||
| Page Range: | pp. 1865-1875 | ||||||||
| DOI: | 10.1109/TVCG.2019.2898823 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Publisher Statement: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
| Access rights to Published version: | Restricted or Subscription Access |
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