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 language | English (US) |
|---|---|
| Title of host publication | Proceedings - Motion in Games 2016 |
| Subtitle of host publication | 9th International Conference on Motion in Games, MIG 2016 |
| Editors | Stephen N. Spencer |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 193-194 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781450345927 |
| DOIs | |
| State | Published - Oct 10 2016 |
| Event | 9th International Conference on Motion in Games, MIG 2016 - San Francisco, United States Duration: Oct 10 2016 → Oct 12 2016 |
Publication series
| Name | Proceedings - Motion in Games 2016: 9th International Conference on Motion in Games, MIG 2016 |
|---|
Other
| Other | 9th International Conference on Motion in Games, MIG 2016 |
|---|---|
| Country/Territory | United States |
| City | San Francisco |
| Period | 10/10/16 → 10/12/16 |
Bibliographical note
Publisher Copyright:© 2016 Copyright held by the owner/author(s).
Keywords
- Computer graphics
- Data-driven facial animation
- Digital character emotion