Statistical Optimization for 3-D Reconstruction from a Single View(<Special Section>Image Recognition and Understanding)
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概要
- 論文の詳細を見る
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.
- 社団法人電子情報通信学会の論文
- 2005-10-01
著者
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KANATANI Kenichi
Department of Computer Science, Okayama University
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Sugaya Yasuyuki
Department Of Information And Computer Sciences Toyohashi University Of Technology
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Sugaya Yasuyuki
Department Of Computer Science Okayama University
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Sugaya Yasuyuki
Department Of Computer Science And Engineering Toyohashi University Of Technology
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Kanatani Kenichi
Okayama Univ. Okayama‐shi Jpn
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Kanatani Kenichi
Department Of Computer Science Gunma University
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