The tesselated spheres in the left image are rendered with two different types of a blue plastic BRDF, yet they are perceived as made from the same material. The objects in the right image are rendered with an identical blue plastic BRDF, yet their appearance is very different.
This paper proposes a method for efficiently rendering indirect highlights. Indirect highlights are caused by the primary light source reflecting off two or more glossy surfaces. Accurately simulating such highlights is important to convey the realistic appearance of materials such as chrome and shiny metal. Our method models the glossy BRDF at a surface point as a directional distribution, using a spherical von Mises-Fisher (vMF) distribution. As our main contribution, we merge multiple vMFs into a combined multimodal distribution. This effectively creates a filtered radiance response function, allowing us to efficiently estimate indirect highlights. We demonstrate our method in a near-interactive application for rendering scenes with highly glossy objects. Our results produce realistic reflections under both local and environment lighting.
The tesselated spheres in the left image are rendered with two different types of a blue plastic BRDF, yet they are perceived as made from the same material. The objects in the right image are rendered with an identical blue plastic BRDF, yet their appearance is very different.
Recent work in interactive global illumination addresses diffuse and moderately glossy indirect lighting effects, but high-frequency effects such as multi-bounce reflections on highly glossy surfaces are often ignored. Accurately simulating such effects is important to convey the realistic appearance of materials such as chrome and shiny metal. In this paper, we present an efficient method for visualizing multi-bounce glossy reflections at interactive rates under environment lighting. Our main contribution is a pre-computation-based method which efficiently gathers subsequent highly glossy reflection passes modelled with a non-linear transfer function representation based on the von Mises-Fisher distribution. We show that our gathering method is superior to scattered sampling.To exploit the sparsity of the pre-computed data, we apply perfect spatial hashing. As a result, we are able to visualize multi-bounce glossy reflections at interactive rates at a low pre-computation cost.
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