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Smooth Surface Reconstruction Using Tensor Fields as Structuring Elements
Author(s) -
Vieira M. B.,
Martins P. P.,
Araújo A. A.,
Cord M.,
PhilippFoliguet S.
Publication year - 2004
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2004.00810.x
Subject(s) - structuring element , estimator , structuring , tensor (intrinsic definition) , surface (topology) , inference , computer science , field (mathematics) , tensor field , surface reconstruction , algorithm , mathematics , artificial intelligence , structure tensor , pattern recognition (psychology) , image (mathematics) , geometry , image processing , mathematical analysis , pure mathematics , mathematical morphology , statistics , finance , economics , exact solutions in general relativity
We propose a new strategy to estimate surface normal information from highly noisy sparse data. Our approach is based on a tensor field morphologically adapted to infer normals. It acts as a three‐dimensional structuring element of smooth surfaces. Robust orientation inference for all input elements is performed by morphological operations using the tensor field. A general normal estimator is defined by combining the inferred normals, their confidences and the tensor field. This estimator can be used to directly reconstruct the surface or give input normals to other reconstruction methods. We present qualitative and quantitative results to show the behavior of the original methods and ours. A comparative discussion of these results shows the efficiency of our propositions.