Hartmut Schirmacher

On‐the‐Fly Processing of Generalized Lumigraphs

We introduce a flexible and powerful concept for reconstructing arbitrary views from multiple source images on the fly. Our approach is based on a Lumigraph structure with per‐pixel depth values, and generalizes the classical two‐plane parameterized light fields and Lumigraphs. With our technique, it is possible to render arbitrary views of time‐varying, non‐diffuse scenes at interactive frame rates, and it allows using any kind of sensor that yields images with dense depth information. We demonstrate the flexibility and efficiency of our approach through various examples.

Adaptive Acquisition of Lumigraphs from Synthetic Scenes

Light fields and Lumigraphs are capable of rendering scenes of arbitrary geometrical or illumination complexity in real time. They are thus interesting ways of interacting with both recorded real‐world and high‐quality synthetic scenes.

Getting Rid of Links in Hierarchical Radiosity

Hierarchical radiosity with clustering has positioned itself as one of the most efficient algorithms for computing global illumination in non‐trivial environments. However, using hierarchical radiosity for complex scenes is still problematic due to the necessity of storing a large number of transport coefficients between surfaces in the form of links. In this paper, we eliminate the need for storage of links through the use of a modified shooting method for solving the radiosity equation. By distributing only unshot radiosity in each step of the iteration, the number of links decreases exponentially. Recomputing these links instead of storing them increases computation time, but reduces memory consumption dramatically. Caching may be used to reduce the time overhead. We analyze the error behavior of the new algorithm in comparison with the normal gathering approach for hierarchical radiosity. In particular, we consider the relation between the global error of a hierarchical radiosity solution and the local error threshold for each link.