Intensity-Based Congealing for Unsupervised Joint Image Alignment. Storer, M., Urschler, M., & Bischof, H. In 2010 20th International Conference on Pattern Recognition, pages 1473-1476, 8, 2010. IEEE. ![Intensity-Based Congealing for Unsupervised Joint Image Alignment [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex We present an approach for unsupervised alignment of an ensemble of images called congealing. Our algorithm is based on image registration using the mutual information measure as a cost function. The cost function is optimized by a standard gradient descent method in a multiresolution scheme. As opposed to other congealing methods, which use the SSD measure, the mutual information measure is better suited as a similarity measure for registering images since no prior assumptions on the relation of intensities between images are required. We present alignment results on the MNIST handwritten digit database and on facial images obtained from the CVL database. © 2010 IEEE.
@inproceedings{
title = {Intensity-Based Congealing for Unsupervised Joint Image Alignment},
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abstract = {We present an approach for unsupervised alignment of an ensemble of images called congealing. Our algorithm is based on image registration using the mutual information measure as a cost function. The cost function is optimized by a standard gradient descent method in a multiresolution scheme. As opposed to other congealing methods, which use the SSD measure, the mutual information measure is better suited as a similarity measure for registering images since no prior assumptions on the relation of intensities between images are required. We present alignment results on the MNIST handwritten digit database and on facial images obtained from the CVL database. © 2010 IEEE.},
bibtype = {inproceedings},
author = {Storer, Markus and Urschler, Martin and Bischof, Horst},
doi = {10.1109/ICPR.2010.364},
booktitle = {2010 20th International Conference on Pattern Recognition}
}
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