2012The Imaging Science JournalRequires access

Globally optimal estimate for variational surface reconstruction

L-C Jin, W-G Wan, X-Q Yu

Open publisher page 1 citations

Abstract

In this article, we tackle the problem of using globally optimal estimate for variational surface reconstruction. We give an overview of globally optimal method on variational surface when the three-dimensional (3D) surface is represented by a point-based surface and a triangular mesh-based surface, and we detail the variational surface used on surface reconstruction. It can be applied to derive a range of meaningful surface reconstructions from this high dimensional space. We show that using a progression of spatially varying anisotropic weights can achieve significant improvements in surface reconstruction. Simulated surfaces and real model are experimentally studied, and the results validate that the proposed approaches improved the reconstruction. The proposed method improved the reconstruction results significantly for the simulated and real data.

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What this paper is about

In this article, we tackle the problem of using globally optimal estimate for variational surface reconstruction. We give an overview of globally optimal method on variational surface when the three-dimensional (3D) surface is represented by a point-based surface and a triangular mesh-based surface, and we detail the variational surface used on surface reconstruction. It can be applied to derive a range of meaningful surface reconstructions from this high dimensional space. We show that using a progression of spatially varying anisotropic weights can achieve significant improvements in surface reconstruction. Simulated surfaces and real model are experimentally studied, and the results validate that the proposed approaches improved the reconstruction. The proposed method improved the reconstruction results significantly for the simulated and real data.

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Available abstract

In this article, we tackle the problem of using globally optimal estimate for variational surface reconstruction. We give an overview of globally optimal method on variational surface when the three-dimensional (3D) surface is represented by a point-based surface and a triangular mesh-based surface, and we detail the variational surface used on surface reconstruction. It can be applied to derive a range of meaningful surface reconstructions from this high dimensional space. We show that using a progression of spatially varying anisotropic weights can achieve significant improvements in surface reconstruction. Simulated surfaces and real model are experimentally studied, and the results validate that the proposed approaches improved the reconstruction. The proposed method improved the reconstruction results significantly for the simulated and real data.

Key concepts: Surface reconstruction, Surface (topology), Range (aeronautics), Point (geometry), Mathematics, Anisotropy, Computer science, Space (punctuation)

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