Efficiently combining positions and normals for precise 3d geometry

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Efficiently combining positions and normals for precise 3d geometry (2005)

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by Diego Nehab , Szymon Rusinkiewicz , James Davis , Ravi Ramamoorthi

Venue:	ACM Transactions on Graphics (Proc. SIGGRAPH
Citations:	131 - 9 self

BibTeX

@ARTICLE{Nehab05efficientlycombining,
    author = {Diego Nehab and Szymon Rusinkiewicz and James Davis and Ravi Ramamoorthi},
    title = {Efficiently combining positions and normals for precise 3d geometry},
    journal = {ACM Transactions on Graphics (Proc. SIGGRAPH},
    year = {2005},
    volume = {24},
    pages = {536--543}
}

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Abstract

not use color information in order to focus on geometric aspects. Note how our method eliminates noise from the range image while introducing real detail. The surface normals are of the same quality or better than those from photometric stereo, while most of the low-frequency bias has been eliminated. Range scanning, manual 3D editing, and other modeling approaches can provide information about the geometry of surfaces in the form of either 3D positions (e.g., triangle meshes or range images) or orientations (normal maps or bump maps). We present an algorithm that combines these two kinds of estimates to produce a new surface that approximates both. Our formulation is linear, allowing it to operate efficiently on complex meshes commonly used in graphics. It also treats high- and low-frequency components separately, allowing it to optimally combine outputs from data sources such as stereo triangulation and photometric stereo, which have different error-vs.-frequency characteristics. We demonstrate the ability of our technique to both recover high-frequency details and avoid low-frequency bias, producing surfaces that are more widely applicable than position or orientation data alone. 1

Keyphrases

photometric stereo range image low-frequency bias low-frequency component surface normal stereo triangulation triangle mesh data source frequency characteristic real detail different error-vs geometric aspect color information high-frequency detail new surface orientation data complex mesh normal map range scanning

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