Merge2-3D: Combining Multiple Normal Maps with 3D Surfaces

3DV), 2014 2nd International Conference  (2014)

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摘要
We propose an approach to enhance rough 3D geometry with fine details obtained from multiple normal maps. We begin with unaligned 2D normal maps and rough geometry, and automatically optimize the alignments through 2-step iterative registration algorithm. We then map the normals onto the surface, correcting and seamlessly blending them together. Finally, we optimize the geometry to produce high-quality 3D models that incorporate the high-frequency details from the normal maps. We demonstrate that our algorithm improves upon the results produced by some well-known algorithms: Poisson surface reconstruction [1] and the algorithm proposed by Nehab et al. [2].
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关键词
computational geometry,image enhancement,image reconstruction,image registration,iterative methods,solid modelling,stochastic processes,2-step iterative registration algorithm,3D models,3D surfaces,Merge2-3D,Poisson surface reconstruction,alignment optimization,mesh enhancement,multiple normal maps,rough 3D geometry enhancement,unaligned 2D normal maps,2.5/3D alignment,mesh enhancement,surface normals
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