PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Quasi-isometric parameterization for texture mapping
Xianfang Sun and Edwin Hancock
Pattern Recognition Volume 41, Number 5, pp. 1732-1743, 2008.

Abstract

In this paper, we present a new 3D triangular mesh parameterization method that is computationally efficient and yields minimized distance errors. The method has four steps. Firstly, multidimensional scaling (MDS) is used to flatten each submesh consisting of one vertex and its direct neighbours on the 3D triangular mesh. Secondly, an optimal method is used to compute the linear reconstructing weights of each vertex with respect to its neighbours. Thirdly, a spectral decomposition method is used to obtain initial 2D parameterization coordinates. Fourthly, the initial coordinates are rotated and scaled to minimize the distance errors. It is demonstrated that this method can be used for texture mapping. Analyses and examples show the effectiveness of this parameterization method compared with alternatives.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Theory & Algorithms
ID Code:6869
Deposited By:Edwin Hancock
Deposited On:08 April 2010