Abstract
Adaptive-size physically based models suitable for nonrigid motion
analysis are presented. The mesh size increases or decreases dynamically
during the surface reconstruction process to locate nodes near surface
areas of interests (like high curvature points) and to optimize the
fitting error. A priori information about nonrigidity can be included so
that the surface model deforms to fit moving data points while
preserving some basic nonrigid constraints (e.g. isometry or
conformality). Implementation of the proposed algorithm with and without
isometric/conformal constraints is presented. Performance and accuracy
of derived algorithms are demonstrated on data simulating deforming
ellipsoidal and bending planar shapes. The algorithm is applied to the
real range data for bending paper and to volumetric temporal left
ventricular data
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