Least squares conformal maps for automatic texture atlas generation
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Conformal Surface Parameterization for Texture Mapping
IEEE Transactions on Visualization and Computer Graphics
Intrinsic Scale Space for Images on Surfaces: The Geodesic Curvature Flow
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Computational Geometry: Theory and Applications
Fundamentals of spherical parameterization for 3D meshes
ACM SIGGRAPH 2003 Papers
Mesh parameterization methods and their applications
Foundations and Trends® in Computer Graphics and Vision
IEEE Transactions on Visualization and Computer Graphics
Geodesic Distance-weighted Shape Vector Image Diffusion
IEEE Transactions on Visualization and Computer Graphics
Intrinsic Geometric Scale Space by Shape Diffusion
IEEE Transactions on Visualization and Computer Graphics
Ricci Flow for 3D Shape Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete surface Ricci flow: theory and applications
Proceedings of the 12th IMA international conference on Mathematics of surfaces XII
Shape-based diffeomorphic registration on hippocampal surfaces using beltrami holomorphic flow
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
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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.