3D-aware Motion Generation of Natural Objects in a Single Omnidirectional Image for Virtual Sightseeing

Services using omnidirectional images have become increasingly popular for virtual sightseeing. For example, Google Street View enables users to view the scenery of a location online without physically visiting it. However, the use of still images in such services limits the sense of presence. This study proposes a method that focuses on natural elements such as water, sky, and trees in a single omnidirectional image and reproduces their motion in 3D space, generating omnidirectional videos to improve the sense of reality in virtual sightseeing. Experiments demonstrate the effectiveness of the proposed method through comparison with a conventional method and user studies.

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Publication Details

Journal
IEICE Transactions on Information and Systems
Published
2025-01-01
DOI
https://doi.org/10.1587/transinf.2025hcp0005
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
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article

3D-aware Motion Generation of Natural Objects in a Single Omnidirectional Image for Virtual Sightseeing

Norihiko Kawai, Motoki Kakuho
IEICE Transactions on Information and Systems
Advanced Vision and Imaging
article

3D-aware Motion Generation of Natural Objects in a Single Omnidirectional Image for Virtual Sightseeing

Norihiko Kawai, Motoki Kakuho
article en

Abstract

Services using omnidirectional images have become increasingly popular for virtual sightseeing. For example, Google Street View enables users to view the scenery of a location online without physically visiting it. However, the use of still images in such services limits the sense of presence. This study proposes a method that focuses on natural elements such as water, sky, and trees in a single omnidirectional image and reproduces their motion in 3D space, generating omnidirectional videos to improve the sense of reality in virtual sightseeing. Experiments demonstrate the effectiveness of the proposed method through comparison with a conventional method and user studies.

IEICE Transactions on Information and Systems
Osaka Institute of Technology (JP)
Openalex Percentile: Top 58%
Advanced Vision and Imaging
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