Mood-Driven Colorization of Virtual Indoor Scenes
One of the challenging tasks in virtual scene design for Virtual Reality (VR) is causing it to invoke a particular mood in viewers. The subjective nature of moods brings uncertainty to the purpose. We propose a novel approach to automatic adjustment of the colors of textures for objects in a virtual...
Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 28(2022), 5 vom: 15. Mai, Seite 2058-2068 |
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Weitere Verfasser: | , , , , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2022
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Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
Schlagworte: | Journal Article |
Zusammenfassung: | One of the challenging tasks in virtual scene design for Virtual Reality (VR) is causing it to invoke a particular mood in viewers. The subjective nature of moods brings uncertainty to the purpose. We propose a novel approach to automatic adjustment of the colors of textures for objects in a virtual indoor scene, enabling it to match a target mood. A dataset of 25,000 images, including building/home interiors, was used to train a classifier with the features extracted via deep learning. It contributes to an optimization process that colorizes virtual scenes automatically according to the target mood. Our approach was tested on four different indoor scenes, and we conducted a user study demonstrating its efficacy through statistical analysis with the focus on the impact of the scenes experienced with a VR headset |
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Beschreibung: | Date Revised 12.04.2022 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
ISSN: | 1941-0506 |
DOI: | 10.1109/TVCG.2022.3150513 |