Show simple item record

dc.contributor.advisorHartley, Thomas
dc.contributor.authorWorrallo, Adam Grant
dc.date.accessioned2020-12-17T14:58:38Z
dc.date.available2020-12-17T14:58:38Z
dc.date.issued2020-09
dc.identifier.urihttp://hdl.handle.net/2436/623838
dc.descriptionA thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.en
dc.description.abstractResearch exploring natural virtual reality interaction has seen significant success in optical tracker-based approaches, enabling users to freely interact using their hands. Optical based trackers can provide users with real-time, high-fidelity virtual hand representations for natural interaction and an immersive experience. However, work in this area has identified four issues: occlusion, field-of-view, stability and accuracy. To overcome the four key issues, researchers have investigated approaches such as using multiple sensors. Research has shown multi-sensor-based approaches to be effective in improving recognition accuracy. However, such approaches typically use statically positioned sensors, which introduce body occlusion issues that make tracking hands challenging. Machine learning approaches have also been explored to improve gesture recognition. However, such approaches typically require a pre-set gesture vocabulary limiting user actions with larger vocabularies hindering real-time performance. This thesis presents an optical hand-based interaction system that comprises two Leap Motion sensors mounted onto a VR headset at different orientations. Novel approaches to the aggregation and validation of sensor data are presented. A machine learning sub-system is developed to validate hand data received by the sensors. Occlusion detection, stability detection, inferred hands and a hand interpolation sub-system are also developed to ensure that valid hand representations are always shown to the user. In addition, a mesh conformation sub-system ensures 3D objects are appropriately held in a user’s virtual hand. The presented system addresses the four key issues of optical sessions to provide a smooth and consistent user experience. The MOT system is evaluated against traditional interaction approaches; gloves, motion controllers and a single front-facing sensor configuration. The comparative sensor evaluation analysed the validity and availability of tracking data, along with each sensors effect on the MOT system. The results show the MOT provides a more stable experience than the front-facing configuration and produces significantly more valid tracking data. The results also demonstrated the effectiveness of a 45-degree sensor configuration in comparison to a front-facing. Furthermore, the results demonstrated the effectiveness of the MOT systems solutions at handling the four key issues with optical trackers.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherUniversity of Wolverhamptonen
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectgesturesen
dc.subjectvirtual realityen
dc.subjecthand interactionen
dc.subjectoptical trackingen
dc.subjectleap motionen
dc.subjectnatural interactionen
dc.subjectocclusionen
dc.subjectmachine learningen
dc.subjectsensor functionen
dc.subjectrealisticen
dc.titleA multiple optical tracking based approach for enhancing hand-based interaction in virtual reality simulationsen
dc.typeThesis or dissertationen
dc.type.qualificationnamePhD
dc.type.qualificationlevelDoctoral
refterms.dateFOA2020-12-17T14:58:39Z


Files in this item

Thumbnail
Name:
Worrallo_PhD_thesis.pdf
Size:
6.348Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International