Cristin-prosjekt-ID: 536305
Sist endret: 18. januar 2019 12:21
Cristin-prosjekt-ID: 536305
Sist endret: 18. januar 2019 12:21
Prosjekt

Measuring and Understanding Visual Appearance

prosjektleder

Jon Yngve Hardeberg
ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet

prosjekteier / koordinerende forskningsansvarlig enhet

  • Norges teknisk-naturvitenskapelige universitet

Klassifisering

Vitenskapsdisipliner

Annen informasjonsteknologi

Emneord

visuelt utseende • farge • glans • Texture • gjennomskinnelighet • måling metrology

Kategorier

Prosjektkategori

  • Faglig utviklingsarbeid
  • Grunnforskning

Tidsramme

Aktivt
Start: 1. mai 2016 Slutt: 30. april 2021

Beskrivelse Beskrivelse

Tittel

Measuring and Understanding Visual Appearance

Populærvitenskapelig sammendrag

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. 

Vitenskapelig sammendrag

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.

Metode

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.

Utstyr

The project supports:

  • 2 PhD candidates
  • 3 Post-doctoral candidates
  • 20% Professor position

The project is lead by the Norwegian Colour and Visual Computing Laboratory at NTNU i Gjøvik. Professor Jon Yngve Hardeberg is the project leader.  

prosjektdeltakere

prosjektleder

Jon Yngve Hardeberg

  • Tilknyttet:
    Prosjektleder
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet

Aland Andres Aguirre Mendoza

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet

Jean-Baptiste Thomas

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet

Giuseppe Claudio Guarnera

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet

Gregory Paul High

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet
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Resultater Resultater

Bidirectional Reflectance Measurement and Reflection Model Fitting of Complex Materials Using an Image-Based Measurement Setup.

Sole, Aditya Suneel; Farup, Ivar; Nussbaum, Peter; Tominaga, Shoji. 2018, Journal of Imaging. NTNUVitenskapelig artikkel

A model of visual opacity for translucent colorants.

Midtfjord, Helene B.; Green, Philip John; Nussbaum, Peter. 2018, Electronic Imaging, Material Appearance 2018 . NTNUVitenskapelig foredrag

Evaluating an image-based bidirectional reflectance distribution function measurement setup.

Sole, Aditya Suneel; Farup, Ivar; Nussbaum, Peter; Tominaga, Shoji. 2018, Applied Optics. CD, NTNUVitenskapelig artikkel

Capturing and representing brdfs for virtual reality.

Guarnera, Dar'ya; Guarnera, Giuseppe Claudio; Ghosh, Abhijeet; Hall, Ian; Glencross, Mashhuda. 2016, SIGGRAPH ASIA 2016. NTNUFaglig foredrag

An Adaptive Combination of Dark and Bright Channel Priors for Single Image Dehazing.

Dravo, Vincent Whannou de; El Khoury, Jessica; Thomas, Jean-Baptiste; Mansouri, Alamin; Hardeberg, Jon Yngve. 2017, Journal of Imaging Science and Technology. UdB, NTNUVitenskapelig artikkel
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