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3DPVT
2004
IEEE

A Statistical Method for Robust 3D Surface Reconstruction from Sparse Data

11 years 11 months ago
A Statistical Method for Robust 3D Surface Reconstruction from Sparse Data
Abstract-General information about a class of objects, such as human faces or teeth, can help to solve the otherwise ill-posed problem of reconstructing a complete surface from sparse 3D feature points or 2D projections of points. We present a technique that uses a vector space representation of shape (3D Morphable Model) to infer missing vertex coordinates. Regularization derived from a statistical approach makes the system stable and robust with respect to noise by computing the optimal tradeoff between fitting quality and plausibility. We present a direct, non-iterative algorithm to calculate this optimum efficiently, and a method for simultaneously compensating unknown rigid transformations. The system is applied and evaluated in two different fields: (1) reconstruction of 3D faces at unknown orientations from 2D feature points at interactive rates, and (2) restoration of missing surface regions of teeth for CAD-CAM production of dental inlays and other medical applications.
Volker Blanz, Albert Mehl, Thomas Vetter, Hans-Pet
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where 3DPVT
Authors Volker Blanz, Albert Mehl, Thomas Vetter, Hans-Peter Seidel
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