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.
|Title of host publication||2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015|
|Publisher||IEEE Computer Society|
|Number of pages||5|
|State||Published - 21 Jul 2015|
|Event||12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States|
Duration: 16 Apr 2015 → 19 Apr 2015
|Name||Proceedings - International Symposium on Biomedical Imaging|
|Conference||12th IEEE International Symposium on Biomedical Imaging, ISBI 2015|
|Period||16/04/15 → 19/04/15|
Bibliographical notePublisher Copyright:
© 2015 IEEE.
- 3D meshes
- Local Depth SIFT
- shape registration