Statistical Optimization for 3-D Reconstruction from a Single View

Kenichi KANATANI  Yasuyuki SUGAYA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E88-D   No.10   pp.2260-2268
Publication Date: 2005/10/01
Online ISSN: 
DOI: 10.1093/ietisy/e88-d.10.2260
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Image Recognition and Understanding)
Category: 
Keyword: 
3-D reconstruction,  statistical optimization,  vanishing point,  vanishing line,  principal point,  

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Summary: 
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.