October 2024
Intermediate
240 pages
6h 57m
Japanese
Content preview from 図解まるわかり VR・AR・MRのしくみ
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120
NeRF、GaussianSplatting
2Dデータから3Dデータを
自動生成
5-18
フォトグラメトリの課題と進化
これまで仮想の物体を現実世界や仮想空間へ表示するために、フォトグ
ラメトリという技術が使われてきました。これは表示したい物体をさまざ
まな角度から撮影して、そのデジタル画像を解析、統合することで3Dモ
デルを作成する方法です。しかし、この方法では輪郭を持たない物体（空
や雲など）や遠くに存在するもの、水や氷などの透明な物体を再現できな
い問題がありました。
そこで登場した技術が、
NeRF（NeuralRadiance Fields） です（ 図
5-35）。AIの一種であるニューラルネットワークを活用して3Dモデルを
作成します。具体的には、多数の2D画像をもとに、ニューラルネットワ
ークが3D空間内の各点における色と透明度を学習します。この情報を用
いることで、任意の視点から3D モデルを生成できるようになります。
フォトグラメトリとの大きな違いは、NeRFではニューラルネットワー
クが3D空間の情報を学習して3Dモデルを作成するという点です。これ
により、フォトグラメトリでは再現が難しかった対象も、より自然に表現
することが可能になります。
現実世界と見間違えるほどの映像描写
高性能なNeRFですが、データ処理に膨大な時間を要するという課題が
ありました。この課題を解決しつつ、高速な画像処理を実現した技術が、
Gaussian Splatting（ガウス・スプラッティング）
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.