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A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms

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5 Author(s)

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

Published in:

Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on  (Volume:1 )

Date of Conference:

17-22 June 2006