When considering global illumination, material editing is a non-linear task and even in scenes with moderate complexity, the global nature of material editing makes final prediction of
appearance of other objects in the scene a difficult task.
In this thesis, a novel interactive method is proposed for object appearance design.
To achieve this, a randomized per-pixel parametrization of scene materials is defined. At rendering time, parametrized materials have different properties for every pixel. This way, encoding of multiple rendered results into one image is obtained. We call this collection of data a hyperimage.
Material editing means projecting the hyperimage onto a given parameter vector, which is achieved using non-linear weighted regression. Pixel guides based on geometry (normals, depth and unique object ID), materials and lighting properties of the scene enter the regression problem as pixel weights. In order to ensure that only relevant features are considered,
a rendering-based feature selection method is introduced, which uses a precomputed pixelfeature
function, encoding per-pixel importance of each parametrized material.
The method of hyperimages is independent of the underlying rendering algorithm, while
supporting a full global illumination and surface interactions.
Our method is not limited to parametrization of materials, and can be extended to other
scene properties. As an example, we show parametrization of position of an area light source.