interior

Reconstructing Building Interiors from Images

Abstract
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, multi-view 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 Manhattan-world 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, including a 3D reconstruction and image-based walk-through of an entire floor of a house, the first result of this kind from an automated computer vision system.

Team

	Yasutaka Furukawa Brian Curless Steven M. Seitz	CSE, Graphics and Imaging Lab (GRAIL), University of Washington
	Richard Szeliski	Interactive Visual Media Group, Microsoft Research

Paper

Yasutaka Furukawa, Brian Curless, Steven M. Seitz, Richard Szeliski
Reconstructing Building Interiors from Images
ICCV 2009 (oral)

Slides

3D Viewer with Gallery dataset for download
omviewer-vista.tgz
I do not have XP machines any more and can compile the programs only for vista. This worked on Windows 7, too.

Movies

Kitchen - 22 images (high-res)	Hall - 97 images (high-res)
Gallery - 492 images (high-res)	All (high-res)

Acknowledgements
This work was supported in part by National Science Foundation grant IIS-0811878, SPAWAR, the Office of Naval Research, the University of Washington Animation Research Labs, and Microsoft. We thank Christian Laforte and Feeling Software for the kitchen dataset. We also thank Eric Carson and Henry Art Gallery for the help with the gallery dataset.

Contact
Send any comments or questions to Yasutaka Furukawa.

Last updated on 2009/09/24