Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27198
Title: Virtual Reality experience design: An emotion driven modelling
Authors: AlHamed, Huda Abdulrahman Abdulla
Advisors: Bell, D
Louvieris, P
Keywords: Artificial intelligence (AI);Data mining;User Experience;( UX) Design;Virtual Reality (VR);Cultural Heritage
Issue Date: 2021
Publisher: Brunel University London
Abstract: Designing a new and engaging virtual reality (VR) experience is a challenging endeavour with diverse stakeholders, hardware platforms and media content. Cultural heritage is an excellent example of this complexity, where perspectives include the visitors, heritage sites (including museum curators and collection managers) and educational staff. This research develops a new design approach supported by practically tested methods and models. Consequently, all perspectives must be included in the design process. VR design research has typically focused on a particular user group or object - with more recent work on the emotional responses to VR expenences. A design science research (DSR) approach is followed throughout. Fishwick's thinking system approach was adopted as a baseline. Object and experience models are subsequently developed, starting with an object model (CHOM) in the first increment. This model was extended further in the second increment with a combination of data and sentiment analysis methods, resulting in a novel Cultural Heritage VR experience (C-Her-VR) model and methodology. Practical user experience (UX) design methods are utilised to construct rich VR experience models that synthesise the varied perspectives of stakeholders. The research has resulted in a novel cultural heritage approach to designing VR experiences. The multi-view approach synthesises stakeholder perspectives utilising current design techniques.
Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London
URI: https://bura.brunel.ac.uk/handle/2438/27198
Appears in Collections:Computer Science
Dept of Computer Science Theses

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