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CVPR
2009
IEEE

Manhattan-world Stereo

11 years 7 months ago
Manhattan-world Stereo
Multi-view stereo (MVS) algorithms now produce reconstructions that rival laser range scanner accuracy. However, stereo algorithms require textured surfaces, and therefore work poorly for many architectural scenes (e.g., building interiors with textureless, painted walls). This paper presents a novel MVS approach to overcome these limitations for Manhattan World scenes, i.e., scenes that consists of piece-wise planar surfaces with dominant directions. Given a set of calibrated photographs, we first reconstruct textured regions using an existing MVS algorithm, then extract dominant plane directions, generate plane hypotheses, and recover per-view depth maps using Markov random fields. We have tested our algorithm on several datasets ranging from office interiors to outdoor buildings, and demonstrate results that outperform the current state of the art for such texture-poor scenes.
Brian Curless, Richard Szeliski, Steven M. Seitz,
Added 06 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Brian Curless, Richard Szeliski, Steven M. Seitz, Yasutaka Furukawa
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