Rotationally Symmetric Operators for Surface Interpolation

The use of rotationally symmetric operators in vision is reviewed and conditions for rotational symmetry are derived for linear and quadratic forms in the first and second partial directional derivatives of a function f(x,y). Surface interpolation is considered to be the process of computing t...

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Egile Nagusiak: Brady, Michael, Horn, Berthold K.P.
Hizkuntza:en_US
Argitaratua: 2004
Sarrera elektronikoa:http://hdl.handle.net/1721.1/6365
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author Brady, Michael
Horn, Berthold K.P.
author_facet Brady, Michael
Horn, Berthold K.P.
author_sort Brady, Michael
collection MIT
description The use of rotationally symmetric operators in vision is reviewed and conditions for rotational symmetry are derived for linear and quadratic forms in the first and second partial directional derivatives of a function f(x,y). Surface interpolation is considered to be the process of computing the most conservative solution consistent with boundary conditions. The "most conservative" solution is modeled using the calculus of variations to find the minimum function that satisfies a given performance index. To guarantee the existence of a minimum function, Grimson has recently suggested that the performance index should be a semi-norm. It is shown that all quadratic forms in the second partial derivatives of the surface satisfy this criterion. The seminorms that are, in addition, rotationally symmetric form a vector space whose basis is the square Laplacian and the quadratic variation. Whereas both seminorms give rise to the same Euler condition in the interior, the quadratic variation offers the tighter constraint at the boundary and is to be preferred for surface interpolation.
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spelling mit-1721.1/63652019-04-12T08:30:23Z Rotationally Symmetric Operators for Surface Interpolation Brady, Michael Horn, Berthold K.P. The use of rotationally symmetric operators in vision is reviewed and conditions for rotational symmetry are derived for linear and quadratic forms in the first and second partial directional derivatives of a function f(x,y). Surface interpolation is considered to be the process of computing the most conservative solution consistent with boundary conditions. The "most conservative" solution is modeled using the calculus of variations to find the minimum function that satisfies a given performance index. To guarantee the existence of a minimum function, Grimson has recently suggested that the performance index should be a semi-norm. It is shown that all quadratic forms in the second partial derivatives of the surface satisfy this criterion. The seminorms that are, in addition, rotationally symmetric form a vector space whose basis is the square Laplacian and the quadratic variation. Whereas both seminorms give rise to the same Euler condition in the interior, the quadratic variation offers the tighter constraint at the boundary and is to be preferred for surface interpolation. 2004-10-04T14:53:23Z 2004-10-04T14:53:23Z 1981-11-01 AIM-654 http://hdl.handle.net/1721.1/6365 en_US AIM-654 9497089 bytes 6792407 bytes application/postscript application/pdf application/postscript application/pdf
spellingShingle Brady, Michael
Horn, Berthold K.P.
Rotationally Symmetric Operators for Surface Interpolation
title Rotationally Symmetric Operators for Surface Interpolation
title_full Rotationally Symmetric Operators for Surface Interpolation
title_fullStr Rotationally Symmetric Operators for Surface Interpolation
title_full_unstemmed Rotationally Symmetric Operators for Surface Interpolation
title_short Rotationally Symmetric Operators for Surface Interpolation
title_sort rotationally symmetric operators for surface interpolation
url http://hdl.handle.net/1721.1/6365
work_keys_str_mv AT bradymichael rotationallysymmetricoperatorsforsurfaceinterpolation
AT hornbertholdkp rotationallysymmetricoperatorsforsurfaceinterpolation