Issue No.03 - May/June (2009 vol.15)

pp: 504-517

Miao Jin , University of Louisiana at Lafayette, Lafayette

Wei Zeng , Stony Brook University, Stony Brook

Feng Luo , Rutgers University, Piscataway

Xianfeng Gu , Stony Brook University, Stony Brook

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2008.103

ABSTRACT

Shape indexing, classification, and retrieval are fundamental problems in computer graphics. This work introduces a novel method for surface indexing and classification based on Teichmuller theory. The Teichmuller space for surfaces with the same topology is a finite dimensional manifold, where each point represents a conformal equivalence class, a curve represents a deformation process from one class to the other. We apply Teichmuller space coordinates as shape descriptors, which are succinct, discriminating and intrinsic; invariant under the rigid motions and scalings, insensitive to resolutions. Furthermore, the method has solid theoretic foundation, and the computation of Teichmuller coordinates is practical, stable and efficient. This work focuses on the surfaces with negative Euler numbers, which have a unique conformal Riemannian metric with -1 Gaussian curvature. The coordinates which we will compute are the lengths of a special set of geodesics under this special metric. The metric can be obtained by the curvature flow algorithm, the geodesics can be calculated using algebraic topological method. We tested our method extensively for indexing and comparison of about one hundred of surfaces with various topologies, geometries and resolutions. The experimental results show the efficacy and efficiency of the length coordinate of the Teichmuller space.

INDEX TERMS

Curve, surface, solid, and object representations, Geometric algorithms, languages, and systems

CITATION

Miao Jin, Wei Zeng, Feng Luo, Xianfeng Gu, "Computing Teichmüller Shape Space",

*IEEE Transactions on Visualization & Computer Graphics*, vol.15, no. 3, pp. 504-517, May/June 2009, doi:10.1109/TVCG.2008.103REFERENCES