Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
We propose a modular framework for robust 3D reconstruction from unorganized, unoriented, noisy, and outlierridden geometric data. We gain robustness and scalability over previous...
Patrick Mullen, Fernando de Goes, Mathieu Desbrun,...
We consider the problem of reconstructing the shape of a surface with an arbitrary, spatially varying isotropic bidirectional reflectance distribution function (BRDF), and introdu...
This paper presents a method that uses the level sets of volumes to reconstruct the shapes of 3D objects from range data. The strategy is to formulate 3D reconstruction as a stati...
Free-form deformations (FFD) constitute an important geometric shape modification method that has been extensively investigated for computer animation and geometric modelling. In t...