@techreport{oai:ipsj.ixsq.nii.ac.jp:00231964,
 author = {松原, 智也 and 杉本, 麻樹 and 斎藤, 英雄 and Tomoya, Matsubara and Maki, Sugimoto and Hideo, Saito},
 issue = {42},
 month = {Jan},
 note = {Metaverse has been attracting more and more attention because of its potential for various use cases. In metaverse applications, the seamless integration of digital and physical worlds is vital for synchronizing information from one world to another. One way to achieve this is to reconstruct 3D environmental maps every time, which is not feasible due to computational complexity. In this paper, we propose a change detection method, combined with object classification, designed for efficiently updating the existing 3D environmental map as little as possible. Despite its simplicity, the experiment shows promising results with an object detector fine-tuned with data from the target environment., Metaverse has been attracting more and more attention because of its potential for various use cases. In metaverse applications, the seamless integration of digital and physical worlds is vital for synchronizing information from one world to another. One way to achieve this is to reconstruct 3D environmental maps every time, which is not feasible due to computational complexity. In this paper, we propose a change detection method, combined with object classification, designed for efficiently updating the existing 3D environmental map as little as possible. Despite its simplicity, the experiment shows promising results with an object detector fine-tuned with data from the target environment.},
 title = {メタバースマップの継続的更新のための差分検出},
 year = {2024}
}