Current interests

Manifold sampling and low-discrepancy methods. Point based graphics and non-photorealistic rendering.

Example Research Title:

Low-discrepancy Sampling for Visual Computing High quality point sampling without the introduction of obvious regularity or structure.

Application Area:

Anisotropic low-discrepancy manifold sampling for non-photorealistic rendering, remeshing and finite element methods.

Research:

Low-discrepancy sampling of manifolds according to user-defined tensor fields.

A manifold is segmented and parameterised according to the field, and aligned to space-filling curves. The curves are then mapped back to the manifold and sampled. The output is an evenly distributed sampling that locally adheres to the anisotropy of the field.

Looking for Commercial Partners:

To expand applications of sampling into measurement and finite element methods.

Collaboration:

Alan Woodland and Fred Labrosse, Aberystwyth University, investigating the properties of image manifolds.  Feng Sun and Wenping Wang, University of Hong Kong, Constrained Voronoi Tesselations and Optimal Delaunay Triangulations.