Large-Scale Modeling of Parametric Surfaces Using Spherical Harmonics

Authors:
Li Shen;Moo K. Chung
Affiliations:
University of Massachusetts Dartmouth, USA;University of Wisconsin Madison, USA
Venue:
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Year:
2006

Citing 0
Cited 5

Technical Section: Fourier method for large-scale surface modeling and registration

Computers and Graphics
Reconstructing 3D Facial Shape Using Spherical Harmonics

ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Topological Correction of Brain Surface Meshes Using Spherical Harmonics

MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
3D shape analysis for early diagnosis of malignant lung nodules

IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
3D shape analysis for early diagnosis of malignant lung nodules

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present an approach for large-scale modeling of parametric surfaces using spherical harmonics (SHs). A standard least square fitting (LSF) method for SH expansion is not scalable and cannot accurately model large 3D surfaces. We propose an iterative residual fitting (IRF) algorithm, and demonstrate its effectiveness and scalability in creating accurate SH models for large 3D surfaces. These large-scale and accurate parametric models can be used in many applications in computer vision, graphics, and biomedical imaging. As a simple extension of LSF, IRF is very easy to implement and requires few machine resources.