Title :
A minimum-variance adaptive surface mesh
Author :
Wilson, Richard C. ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
Abstract :
The main contribution of the paper is to describe a new class of the adaptive mesh. The mesh uses both split and merge operations to adapt itself to the structure of volumetric data-points. The adaptive behaviour is controlled by the variance of the data-point positions about maximum-likelihood quadric patches. The authors show that the density of control points on the mesh is regulated by the curvature of the underlying surface. Finally, they illustrate the effectiveness of the method on both real-world and simulated data-sets
Keywords :
image reconstruction; maximum likelihood estimation; merging; control point density; data point position variance; maximum-likelihood quadric patches; merge operations; minimum-variance adaptive surface mesh; real-world data sets; simulated data sets; split operations; surface curvature; volumetric data points; Adaptive control; Computer science; Equations; Finite element methods; Lagrangian functions; Programmable control; Spline; Surface fitting; Surface reconstruction; Topology;
Conference_Titel :
Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
Conference_Location :
San Juan
Print_ISBN :
0-8186-7822-4
DOI :
10.1109/CVPR.1997.609392
