Multi-Layer Scene Representation from Composed Focal Stacks
Multi-layer images are a powerful scene representation for high-performance rendering in virtual/augmented reality (VR/AR). The major approach to generate such images is to use a deep neural network trained to encode colors and alpha values of depth certainty on each layer using registered multi-vie...
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 29(2023), 11 vom: 02. Nov., Seite 4719-4729 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
| Schlagworte: | Journal Article |
| Zusammenfassung: | Multi-layer images are a powerful scene representation for high-performance rendering in virtual/augmented reality (VR/AR). The major approach to generate such images is to use a deep neural network trained to encode colors and alpha values of depth certainty on each layer using registered multi-view images. A typical network is aimed at using a limited number of nearest views. Therefore, local noises in input images from a user-navigated camera deteriorate the final rendering quality and interfere with coherency over view transitions. We propose to use a focal stack composed of multi-view inputs to diminish such noises. We also provide theoretical analysis for ideal focal stacks to generate multi-layer images. Our results demonstrate the advantages of using focal stacks in coherent rendering, memory footprint, and AR-supported data capturing. We also show three applications of imaging for VR |
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| Beschreibung: | Date Revised 03.11.2023 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0506 |
| DOI: | 10.1109/TVCG.2023.3320248 |