Title :
Spherical diffusion for 3D surface smoothing
Author_Institution :
Philips Res. Lab., Hamburg, Germany
Abstract :
A diffusion-based approach to surface smoothing is presented. Surfaces are represented as scalar functions defined on the sphere. The approach is equivalent to Gaussian smoothing on the sphere and is computationally efficient since it does not require iterative smoothing. Furthermore, it does not suffer from the well-known shrinkage problem. Evolution of important shape features (parabolic curves) under diffusion is demonstrated. A nonlinear modification of the diffusion process is introduced in order to improve smoothing behavior of elongated and poorly centered objects.
Keywords :
Gaussian processes; smoothing methods; stereo image processing; 3D surface smoothing; Gaussian smoothing; nonlinear modification; parabolic curves features; scalar functions; smoothing behavior; spherical diffusion; Computer vision; Data acquisition; Diffusion processes; Image processing; Iterative methods; Kernel; Laplace equations; Laser modes; Shape; Smoothing methods; Index Terms- Surface smoothing; diffusion; spherical harmonics.; Cephalometry; Head; Humans; Models, Anatomic; Pattern Recognition, Automated;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2004.129