Learning Image Alignment without Local Minima for Face Detection and Tracking

Minh Hoai Nguyen and Fernando De la Torre Frade
8th IEEE International Conference on Automatic Face and Gesture Recognition, October, 2008.


Download
  • Adobe portable document format (pdf) (980KB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract
Active Appearance Models (AAMs) have been extensively used for face alignment during the last 20 years. While AAMs have numerous advantages relative to alternate approaches, they suffer from two major drawbacks: (i) AAMs are especially prone to local minima in the fitting process; (ii) few if any of the local minima of the cost function correspond to acceptable solutions. To minimize these problems, this paper proposes a method to learn the fitting cost function that explicitly optimizes that the local minima occur at and only at the places corresponding to the correct fitting parameters. The paper explores two methods to parameterize the cost function: pixel weighting and subspace learning. Experiments on synthetic and real data show the effectiveness of our approach for face alignment.

Notes
Sponsor: U.S. Naval Research Laboratory, National Institute of Health Grant
Grant ID: N00173-07-C-2040, R01 MH 051435
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): Human Sensing, Face Group, Component Analysis
Associated Project(s): Facial Feature Detection and Deception Detection

Text Reference
Minh Hoai Nguyen and Fernando De la Torre Frade, "Learning Image Alignment without Local Minima for Face Detection and Tracking," 8th IEEE International Conference on Automatic Face and Gesture Recognition, October, 2008.

BibTeX Reference
@inproceedings{Nguyen_2008_6186,
   author = "Minh Hoai Nguyen and Fernando {De la Torre Frade}",
   title = "Learning Image Alignment without Local Minima for Face Detection and Tracking",
   booktitle = "8th IEEE International Conference on Automatic Face and Gesture Recognition",
   month = "October",
   year = "2008",
}