Increasing the Density of Active Appearance Models

Active Appearance Models (AAMs) typically only use 50-100 mesh vertices because they are usually constructed from a set of training images with the vertices hand-labeled on them. In this paper, we propose an algorithm to increase the density of an AAM. Our algorithm operates by iteratively building the AAM, refitting the AAM to the training data, and refining the AAM.We compare our algorithm with the state of the art in optical flow algorithms and find it to be significantly more accurate. We also show that dense AAMs can be fit more robustly than sparse ones. Finally, we show how our algorithm can be used to construct AAMs automatically, starting with a single affine model that is subsequently refined to model non-planarity and non-rigidity.

increasing_cvpr_08.pdf
PDF file

In  Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

Publisher  IEEE Computer Society
Copyright © 2007 IEEE. Reprinted from IEEE Computer Society. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Details

TypeInproceedings
URLhttp://www.computer.org/portal/site/ieeecs/index.jsp
> Publications > Increasing the Density of Active Appearance Models