In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
This paper addresses the probabilistic inference of geometric structures from images. Specifically, of synthesizing range data to enhance the reconstruction of a 3D model of an in...
We develop a novel method for fitting high-resolution template meshes to detailed human body range scans with sparse 3D markers. We formulate an optimization problem in which the ...
Though realistic eulerian fluid simulation systems now provide believable movements, straightforward renderable surface representation, and affordable computation costs, they are...
Rendering large trimmed NURBS models with high quality at interactive frame rates is of great interest for industry, since nearly all their models are designed on the basis of thi...