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Statistical Optimization for 3-D Reconstruction from a Single View
Kenichi KANATANI Yasuyuki SUGAYA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2005/10/01
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Image Recognition and Understanding)
3-D reconstruction, statistical optimization, vanishing point, vanishing line, principal point,
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We analyze the noise sensitivity of the focal length computation, the principal point estimation, and the orthogonality enforcement for single-view 3-D reconstruction based on vanishing points and orthogonality. We point out that due to the nonlinearity of the problem the standard statistical optimization is not very effective. We present a practical compromise for avoiding the computational failure and preserving high accuracy, allowing a consistent 3-D shape in the presence of however large noise.