EDBT 2026 Demo / reviewers in the wild / expert
Simon Finnie
dblp:282/7109
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 50% Computational photography and imaging · 50% | |
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
depth estimation |
0.7 | 1 | 2023 | Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera · IEEE Trans. Vis. Comput. Graph. 2023 |
Computational photography and imaging › panoramic imaging
360° panoramas |
0.7 | 1 | 2023 | Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera · IEEE Trans. Vis. Comput. Graph. 2023 |
Virtual and augmented reality › immersive video
6dof video |
0.7 | 1 | 2023 | Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera · IEEE Trans. Vis. Comput. Graph. 2023 |
Virtual and augmented reality › immersive video
free-viewpoint video |
0.7 | 1 | 2023 | Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera · IEEE Trans. Vis. Comput. Graph. 2023 |
Computational photography and imaging
omnidirectional imaging |
0.7 | 1 | 2023 | Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera · IEEE Trans. Vis. Comput. Graph. 2023 |
Methods — techniques the papers use, named apart from their topics
photogrammetry · 1.3image-based rendering · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° CameraabstractSix degrees-of-freedom (6-DoF) video provides telepresence by enabling users to move around in the captured scene with a wide field of regard. Compared to methods requiring sophisticated camera setups, the image-based rendering method based on photogrammetry can work with images captured with any poses, which is more suitable for casual users. However, existing image-based rendering methods are based on perspective images. When used to reconstruct 6-DoF views, it often requires capturing hundreds of images, making data capture a tedious and time-consuming process. In contrast to traditional perspective images, 360° images capture the entire surrounding view in a single shot, thus, providing a faster capturing process for 6-DoF view reconstruction. This article presents a novel method to provide 6-DoF experiences over a wide area using an unstructured collection of 360° panoramas captured by a conventional 360° camera. Our method consists of 360° data capturing, novel depth estimation to produce a high-quality spherical depth panorama, and high-fidelity free-viewpoint generation. We compared our method against state-of-the-art methods, using data captured in various environments. Our method shows better visual quality and robustness in the tested scenes. Rongsen Chen, Simon Finnie, Andrew Chalmers, Taehyun Rhee |
IEEE Trans. Vis. Comput. Graph. | 3 |