Emotionally aware automated portrait painting

Simon Colton, Michel F. Valstar, Maja Pantic

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

33 Citations (Scopus)

Abstract

We combine a machine vision system that recognises emotions and a non-photorealistic rendering (NPR) system to automatically produce portraits which heighten the emotion of the sitter. To do this, the vision system analyses a short video clip of a person expressing an emotion, then tracks the movement of facial features and uses this tracking data to analyse which emotion was expressed and what the temporal dynamics of the expression were. The image where the emotion is expressed strongest, the location of the facial features in that image and a keyword describing the emotion detected are passed to the NPR software. This keyword is used to choose appropriate (simulated) art materials, colour palettes, abstraction methods and painting styles, so that the rendered image may heighten the emotion being expressed. We describe the vision and rendering systems and their combination, and provide examples of portraits produced in this emotionally aware fashion.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Digital Interactive Media in Entertainment and Arts, DIMEA 2008
Pages304-311
Number of pages8
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event3rd International Conference on Digital Interactive Media in Entertainment and Arts, DIMEA 2008 - Athens, Greece
Duration: 10 Sep 200812 Sep 2008

Publication series

NameProceedings - 3rd International Conference on Digital Interactive Media in Entertainment and Arts, DIMEA 2008

Conference

Conference3rd International Conference on Digital Interactive Media in Entertainment and Arts, DIMEA 2008
CountryGreece
CityAthens
Period10/09/0812/09/08

Keywords

  • Affective computing
  • Computational creativity
  • Emotion detection
  • Machine vision
  • Non-photorealistic rendering

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