| Literature DB >> 24019739 |
X Chen1, H He, G Zou, X Zhang, X Gu, J Hua.
Abstract
This paper presents an improved Euclidean Ricci flow method for spherical parameterization. We subsequently invent a scale space processing built upon Ricci energy to extract robust surface features for accurate surface registration. Since our method is based on the proposed Euclidean Ricci flow, it inherits the properties of Ricci flow such as conformality, robustness and intrinsicalness, facilitating efficient and effective surface mapping. Compared with other surface registration methods using curvature or sulci pattern, our method demonstrates a significant improvement for surface registration. In addition, Ricci energy can capture local differences for surface analysis as shown in the experiments and applications.Entities:
Keywords: Discrete Ricci flow; surface; surface parameterization
Year: 2013 PMID: 24019739 PMCID: PMC3765039 DOI: 10.1016/j.cviu.2013.02.010
Source DB: PubMed Journal: Comput Vis Image Underst ISSN: 1077-3142 Impact factor: 3.876