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2006
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A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms

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A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
This paper presents a quantitative comparison of several multi-view stereo reconstruction algorithms. Until now, the lack of suitable calibrated multi-view image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multi-view stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties. We then describe our process for acquiring and calibrating multiview image datasets with high-accuracy ground truth and introduce our evaluation methodology. Finally, we present the results of our quantitative comparison of state-of-the-art multi-view stereo reconstruction algorithms on six benchmark datasets. The datasets, evaluation details, and instructions for submitting new models are available online at http://vision.middlebury.edu/mview.
Steven M. Seitz, Brian Curless, James Diebel, Dani
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where CVPR
Authors Steven M. Seitz, Brian Curless, James Diebel, Daniel Scharstein, Richard Szeliski
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