Groupwise Diffeomorphic Non-Rigid Registration for Automatic Model Building
Abstract
We describe a framework for registering a group of images together using a set of non-linear diffeomorphic warps. The result of the groupwise registration is an implicit definition of dense correspondences between all of the images in a set, which can be used to construct statistical models of shape change across the set, avoiding the need for manual annotation of training images. We give examples on two datasets (brains and faces) and show the resulting models of shape and appearance variation. We show results of experiments demonstrating that the groupwise approach gives a more reliable correspondence than pairwise matching alone.
Cite
Text
Cootes et al. "Groupwise Diffeomorphic Non-Rigid Registration for Automatic Model Building." European Conference on Computer Vision, 2004. doi:10.1007/978-3-540-24673-2_26Markdown
[Cootes et al. "Groupwise Diffeomorphic Non-Rigid Registration for Automatic Model Building." European Conference on Computer Vision, 2004.](https://mlanthology.org/eccv/2004/cootes2004eccv-groupwise/) doi:10.1007/978-3-540-24673-2_26BibTeX
@inproceedings{cootes2004eccv-groupwise,
title = {{Groupwise Diffeomorphic Non-Rigid Registration for Automatic Model Building}},
author = {Cootes, Timothy F. and Marsland, Stephen and Twining, Carole J. and Smith, Kate and Taylor, Christopher J.},
booktitle = {European Conference on Computer Vision},
year = {2004},
pages = {316-327},
doi = {10.1007/978-3-540-24673-2_26},
url = {https://mlanthology.org/eccv/2004/cootes2004eccv-groupwise/}
}