Matching and Painting using Gestalt Models

Lead Research Organisation: University of Bath
Department Name: Computer Science

Abstract

When an artist makes a drawing or painting of the real world in front of them, they constantly compare what they see to their art. They retouch their art, sometimes to make it more accurate, other times to bring out parts of the scene that interest them. The point is that making art involves seeing somethings as more important than others, and requires an ability to match artwork to the real world. If we replace the artist by a computer we should expect the same things to be true, but at the moment this is not the case. Our proposal is to match photographs and artwork so machines can make better - and new - art. Doing so offers more benefits than producing better artwork, it is a basic technique we can use to help machines identify important parts of a photograph, which helps computers see the world through human eyes just a little more.

Publications

10 25 50
 
Description 1. It is possible to define Pr?gnanz in a computationally useful way.2. Shape is a determining factor in object recognition and in painting.3. Structure is a determining factor in object recognition and in painting.4. Aesthetic value judgments are not arbitrary.
Exploitation Route A computational definition of Pr?gnanz is of value to those who wish to analyse image parts into semantic objects.
Sectors Creative Economy,Culture, Heritage, Museums and Collections