Skip to main content

Computationally rendered painterly portrait spaces

Resource type
Date created
2008-10
Authors/Contributors
Abstract
This work is ongoing output from research work by Steve DiPaola that attempts to build a computational painting system (called ‘painterly’) that allows aspects of art (the creative human act of fine art painting) and science (cognition, vision and perception; as well as computational design) to both enhance and validate each other. The research takes a novel approach to non photorealistic rendering (NPR) which relies on parameterizing a semantic knowledge space of how a human painter paints, that is, the creative and cognitive process.
Document
Copyright statement
Copyright is held by the author(s).
Peer reviewed?
No
Language
English
Member of collection
Download file Size
dipaola-computationallyrendered.pdf 92.51 KB

Views & downloads - as of June 2023

Views: 0
Downloads: 0