Reconstructing Surfaces Using Anisotropic Basis Functions

Point sets obtained from computer vision techniques are often noisy and non-uniform. We present a new method of surface reconstruction that can handle such data sets using anisotropic basis functions. Our reconstruction algorithm draws upon the work in variational implicit surfaces for constructing smooth and seamless 3D surfaces. Implicit functions are often formulated as a sum of weighted basis functions that are radially symmetric. Using radially symmetric basis functions inherently assumes, however, that the surface to be reconstructed is, everywhere, locally symmetric. Such an assumption is true only at planar regions, and hence, reconstruction using isotropic basis is insufficient to recover objects that exhibit sharp features. We preserve sharp features using anisotropic basis that allow the surface to vary locally. The reconstructed surface is sharper along edges and at corner points. We determine the direction of anisotropy at a point by performing principal component analysi...

• Type: Conference
• Year: 2001
• Where: ICCV
• Authors: Huong Quynh Dinh, Greg Turk, Gregory G. Slabaugh
• Keywords: Anisotropic Basis Functions, Computer Vision, ICCV 2001, Surface Reconstruction, Symmetric Basis Functions, Variational Implicit Surfaces, Weighted Basis Functions