Title :
Intrinsic parameters for surface representation using deformable models
Author :
Vemuri, Baba C. ; Malladi, Ravikanth
Author_Institution :
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
Abstract :
A canonical intrinsic parameterization that provides a consistent, invariant form for describing surfaces is defined and constructed using an elastically deformable model. The salient features of this method are that it provides a unified and general framework for reparameterization of a surface and easily allows for incorporation of multiview data sets. The canonical parameterization of the surface is defined in terms of the surface lines of curvature. Depth constraints are first imposed as an external force field on the deformable model that molds itself to be consistent with the data. Principal vectors computed from this conformed model surface are then imposed as a force field on the parameter curves of the model. The parameter curves deform to become tangential to the principal vectors thereby yielding an invariant surface parameterized by the lines of curvature. Extension of the canonical parametric grid to multiple views is demonstrated by incorporating depth and curvature constraints from multiple views
Keywords :
computational complexity; computer vision; surface fitting; canonical intrinsic parameterization; canonical parametric grid; depth constraints; elastically deformable model; external force field; multiview data sets; reparameterization; surface lines of curvature; surface representation; vectors; Computational complexity; Computer vision; Deformable models; Linear systems; Nonlinear equations; Nonlinear systems; Reconstruction algorithms; Shape; Surface fitting; Surface reconstruction;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on