Adaptive-size physically-based models for nonrigid motion analysis

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