| Autor: |
Sverker Rasmuson, Erik Sintorn, Ulf Assarsson |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Computer Science, Vol 4 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2624-9898 |
| DOI: |
10.3389/fcomp.2022.871808 |
| Popis: |
We present a novel way of approaching image-based 3D reconstruction based on radiance fields. The problem of volumetric reconstruction is formulated as a non-linear least-squares problem and solved explicitly without the use of neural networks. This enables the use of solvers with a higher rate of convergence than what is typically used for neural networks, and fewer iterations are required until convergence. The volume is represented using a grid of voxels, with the scene surrounded by a hierarchy of environment maps. This makes it possible to get clean reconstructions of 360° scenes where the foreground and background is separated. A number of synthetic and real scenes from well-known benchmark-suites are successfully reconstructed with quality on par with state-of-the-art methods, but at significantly reduced reconstruction times. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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