Measuring and Understanding Visual Appearance

Humans have the amazing capability to identify which material an object is made of, just by looking at it (for instance metal, plastic, rubber, wood, glass, or fabric). In addition, also based only on its visual appearance, we can often evaluate key properties of the material, such as if it is fragile or robust, soft or hard, slippery or grippy, rotten or fresh, etc. This so-called material perception is an important function of the human visual system, and its evolution has enabled us to assess the environment surrounding us, and to survive in it.

The visual appearance of a material is generally classified into four appearance attributes (colour, gloss, texture, and trans­lucency) that interact with each other. This interaction is very complex and processed by the brain together with other information such as memory and viewing environment, to finally determine the per­ceived appearance of a surface or object.

The concept of visual appearance is currently far from fully understood, neither from the metrological nor perceptual point of view. The goal of this project is to gain new knowledge of how human beings perceive the visual appearance of materials, objects, and scenes, and to develop new methodologies for measuring and communicating visual appearance and appearance-related material and object properties. 

MUVApp is a fundamental research project aimed at measuring and understanding Visual appearance of materials. The primary goal of this project is to gain new knowledge on how humans perceive the visual appearance of materials, objects, and scences, and to develop new methodologies for measuring and communicating visual appearance and appearance-related material and object properties.

This project aims to develop methodology to expand key knowledge and understanding in the field of visual appearance reproduction and develop methodology to measure material appearance. To realise the research objectives of this project the project is divided into two workpackages. The first work package contributes towards developing measurement techniques and protocols to quantify and predict the visual appearance attributes colour, texture, gloss and translucency. The second work package contributes towards finding metrics that have not only high correlation with human material perception calculated from the optical material properties measured in the first work package, but also can consistently predict the perceptual difference between the original and reproduction across attributes of material perception including colour and gloss.

Four renowned academic formal partner organizations and their leading researcher are committed, namely Holly Rushmeier from Yale University, Karl Gegenfurtner from Justus Liebig University Giessen, Gaël Obein from the Conservatoire National des Arts et Métiers, and Shoji Tominaga from Chiba University. These partners will contribute in this project, each with specific qualities to enhance the overall quality of the team, by bringing in complementary skills, competencies, laboratories, and resources.