Abstract
A framework for embedded recognition of faces and facial expressions is described. Faces are modeled based on the appearances and positions of facial features. Hidden states are used to represent discrete facial expressions. A face model is constructed for each person in the database using video segments showing different facial expressions. Face recognition and facial expression recognition are carried out using Bayesian classification. In our current implementation, the face is divided into 9 facial features grouped in 4 regions which are detected and tracked automatically in video segments. We report results on face and facial expression recognition using a video database of 18 people and 6 expressions.
| Original language | English (US) |
|---|---|
| Pages | 633-637 |
| Number of pages | 5 |
| State | Published - 1999 |
| Externally published | Yes |
| Event | International Conference on Image Processing (ICIP'99) - Kobe, Jpn Duration: Oct 24 1999 → Oct 28 1999 |
Other
| Other | International Conference on Image Processing (ICIP'99) |
|---|---|
| City | Kobe, Jpn |
| Period | 10/24/99 → 10/28/99 |
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering