写真測量とリモートセンシング
Online ISSN : 1883-9061
Print ISSN : 0285-5844
ISSN-L : 0285-5844
小特集「NeRFと3D Gaussian Splatting」~機械学習による多視点画像からの3次元モデル再構築技術~
4. NeRFの応用事例の紹介
蘇 姝
著者情報
ジャーナル フリー

2024 年 63 巻 4 号 p. 129-133

詳細
抄録

NeRF (Neural Radiance Fields) has been attracting attention due to recent advancements in 3D scene reconstruction technology. This method uses a fully-connected deep network to generate images from arbitrary viewpoints, using photographs captured from multiple perspectives. Specifically, it learns the position (x, y, z) and viewing direction (θ, φ) of each point in the captured images and estimates the density and color of each point within the 3D space. This enables high-quality reconstruction of complex scenes, a task that traditional techniques struggled with. NeRF shows promise for applications in diverse fields such as surveying, autonomous driving, robotics, medical imaging, entertainment, and more. This article introduces specific applications of NeRF and explains in detail how it is used in various fields.

著者関連情報
© 2024 一般社団法人 日本写真測量学会
前の記事 次の記事
feedback
Top