Simon Finnie

dblp:282/7109 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
depth estimation
0.712023
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
0.712023
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
0.712023
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
0.712023
Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera · IEEE Trans. Vis. Comput. Graph. 2023
Computational photography and imaging
omnidirectional imaging
0.712023
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
YearPublicationVenuePosition
2023 Casual 6-DoF: Free-Viewpoint Panorama Using a Handheld 360° Camera
abstract
Six 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