@inproceedings{d7a187f7b87b42618d585c94e17fe7b9,
title = "Automatic anatomical shape correspondence and alignment using mesh features",
abstract = "In this work, we propose a fully automatic and computationally efficient group registration approach for sets of three-dimensional models represented as mesh objects. Our approach is based on agglomerating the set of pairwise model-to-model rigid registrations by a robust spectral synchronization scheme. The pairwise registration is computed using spectral graph matching applied to meshes via the LD-SIFT local mesh features. We applied the proposed scheme to sets of subcortical surfaces, and it was shown to provide accurate and robust registration results.",
keywords = "3D meshes, Local Depth SIFT, SIFT, shape registration",
author = "Tal Darom and Yaniv Gur and Chen Hajaj and Yosi Keller",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "10.1109/ISBI.2015.7164169",
language = "אנגלית",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "1530--1534",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
address = "ארצות הברית",
}