A data-driven method for variation in animated smiles (extended abstract)

Nick Sohre, Stephen J Guy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Animated digital characters play an important role in virtual experiences. In this work, we utilize data from a large scale user study as training data for a generative model for producing a variety of animated smiles. Our method involves a four stage process that samples a variety of facial expressions,and annotates them with perceived happiness from the user study. The expressions are then transformed into a standardized space and used by a non-parametric classifier to predict happiness of new smiles.

Original languageEnglish (US)
Title of host publicationProceedings - Motion in Games 2016
Subtitle of host publication9th International Conference on Motion in Games, MIG 2016
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
Pages193-194
Number of pages2
ISBN (Electronic)9781450345927
DOIs
StatePublished - Oct 10 2016
Event9th International Conference on Motion in Games, MIG 2016 - San Francisco, United States
Duration: Oct 10 2016Oct 12 2016

Publication series

NameProceedings - Motion in Games 2016: 9th International Conference on Motion in Games, MIG 2016

Other

Other9th International Conference on Motion in Games, MIG 2016
Country/TerritoryUnited States
CitySan Francisco
Period10/10/1610/12/16

Bibliographical note

Funding Information:
This work has been supported in part by the National Science Foundation through grant #CHS-1526693

Publisher Copyright:
© 2016 Copyright held by the owner/author(s).

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Keywords

  • Computer graphics
  • Data-driven facial animation
  • Digital character emotion

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