MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

DeepSpace: Mood-Based Image Texture Generation for Virtual Reality from Music

Author(s)
Sra, Misha; Vijayaraghavan, Prashanth; Rudovic, Ognjen; Maes, Pattie; Roy, Deb
Thumbnail
DownloadPublished version (608.2Kb)
Publisher Policy

Publisher Policy

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

Terms of use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Metadata
Show full item record
Abstract
© 2017 IEEE. Affective virtual spaces are of interest for many VR applications in areas of wellbeing, art, education, and entertainment. Creating content for virtual environments is a laborious task involving multiple skills like 3D modeling, texturing, animation, lighting, and programming. One way to facilitate content creation is to automate sub-processes like assignment of textures and materials within virtual environments. To this end, we introduce the DeepSpace approach that automatically creates and applies image textures to objects in procedurally created 3D scenes. The main novelty of our DeepSpace approach is that it uses music to automatically create kaleidoscopic textures for virtual environments designed to elicit emotional responses in users. Specifically, DeepSpace exploits the modeling power of deep neural networks, which have shown great performance in image generation tasks, to achieve mood-based image generation. Our study results indicate the virtual environments created by DeepSpace elicit positive emotions and achieve high presence scores.
Date issued
2017-07
URI
https://hdl.handle.net/1721.1/137440
Department
Massachusetts Institute of Technology. Media Laboratory
Publisher
IEEE
Citation
Sra, Misha, Vijayaraghavan, Prashanth, Rudovic, Ognjen, Maes, Pattie and Roy, Deb. 2017. "DeepSpace: Mood-Based Image Texture Generation for Virtual Reality from Music."
Version: Final published version

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Facebook Instagram YouTube RSS

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.