Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Defining sharp features in a given 3D model facilitates a better understanding of the surface and aids visualizations, reverse engineering, filtering, simplification, non-photo...
Joel Daniels II, Linh K. Ha, Tilo Ochotta, Cl&aacu...
Computing smooth and optimal one-to-one maps between surfaces of same topology is a fundamental problem in graphics and such a method provides us a ubiquitous tool for geometric mo...
In this paper, we propose a new and powerful shape denoising technique for processing surfaces approximated by triangle meshes and soups. Our approach is inspired by recent non-lo...
Shin Yoshizawa, Alexander G. Belyaev, Hans-Peter S...
Abstract--We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Rie...