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2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06)
Multi-View Stereo Revisited
New York, NY
June 17-June 22
ISBN: 0-7695-2597-0
Michael Goesele, University of Washington
Brian Curless, University of Washington
Steven M. Seitz, University of Washington
We present an extremely simple yet robust multi-view stereo algorithm and analyze its properties. The algorithm first computes individual depth maps using a window-based voting approach that returns only good matches. The depth maps are then merged into a single mesh using a straightforward volumetric approach. We show results for several datasets, showing accuracy comparable to the best of the current state of the art techniques and rivaling more complex algorithms.
Citation:
Michael Goesele, Brian Curless, Steven M. Seitz, "Multi-View Stereo Revisited," cvpr, vol. 2, pp.2402-2409, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06), 2006
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