Abstract
A method based on sequential importance sampling is proposed for tracking facial features on a grid with Gabor attributes. The motion of facial feature points is modeled as a global 2-D affine transformation (accounting for head motion) plus a local deformation (accounting for residual motion due to inaccuracies in 2-D affine modeling and other factors such as facial expression). Motion of both types is estimated simultaneously by the tracker: global motion is tracked by importance sampling, and residual motion is handled by incorporating local deformation into the measurement likelihood in computing the weight of a sample. While it has other applications in facial analysis, the method is particularly applicable to face verification because of a novel parametrization.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE International Conference on Image Processing |
| Pages | 45-48 |
| Number of pages | 4 |
| Volume | 1 |
| State | Published - 2000 |
| Externally published | Yes |
| Event | International Conference on Image Processing (ICIP 2000) - Vancouver, BC, Canada Duration: Sep 10 2000 → Sep 13 2000 |
Other
| Other | International Conference on Image Processing (ICIP 2000) |
|---|---|
| Country/Territory | Canada |
| City | Vancouver, BC |
| Period | 9/10/00 → 9/13/00 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Hardware and Architecture
- Electrical and Electronic Engineering