Reconstructing Building Interiors from Images

This paper proposes a fully automated 3D reconstruction and visualization system for architectural scenes (interiors and exteriors). The reconstruction of indoor environments from photographs is particularly challenging due to texture-poor planar surfaces such as uniformly-painted walls. Our system first uses structure-from-motion, multiview stereo, and a stereo algorithm specifically designed for Manhattan-world scenes (scenes consisting predominantly of piece-wise planar surfaces with dominant directions) to calibrate the cameras and to recover initial 3D geometry in the form of oriented points and depth maps. Next, the initial geometry is fused into a 3D model with a novel depth-map integration algorithm that, again, makes use of Manhattanworld assumptions and produces simplified 3D models. Finally, the system enables the exploration of reconstructed environments with an interactive, image-based 3D viewer. We demonstrate results on several challenging datasets, inclu...

• Type: Conference
• Year: 2009
• Where: ICCV
• Authors: Yasutaka Furukawa, Brian Curless, Steven M. Seitz, Richard Szeliski
• Keywords: 3D Reconstruction, Architectural Scenes, Computer Vision, ICCV 2009