The main goal of this project is to identify relationships between human perception of real-world materials properties and corresponding computational features. We will use Bidirectional Texture Functions as state-of-the-art digital representation of illumination and view dependent real-world material appearance as initial data for our analysis. We believe that rigorous analysis of human perception of individual visual effects in different material samples will allow us not only understand principles of human perception of real material surfaces but also to develop more efficient acquisition, modelling, and editing methods for this type of massive but highly photorealistic data.
The observed material properties are surface specularity, translucency, roughness, anisotropy, directionality, back-scattering, among others. We will study the perceptual importance of these properties as well as their mutual dependency and dependency on type of material and illumination and viewing conditions. We will use established models of low-level human perception, however, we will also exploit psychophysical studies as a main source of knowledge about the way how human observers perceive more complex material surface properties. Our long-term goal is a development of flexible and efficient material sample measurement setup that takes advantage of obtained knowledge about human perception of individual types of real-materials to produce their very accurate but significantly reduced and thus easily applicable digital representation.
The focus of this project is very relevant to the airspace / automotive industry and architecture for safety simulations and photorealistic accurate interior / exterior design applications as well as for galleries and museums for accurate digital representation of culture heritage objects appearance.
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