Parallel Transport of Deformations in Shape Space of Elastic Surfaces
Abstract
Statistical shape analysis develops methods for comparisons, deformations, summarizations, and modeling of shapes in given data sets. These tasks require a fundamental tool called parallel transport of tangent vectors along arbitrary paths. This tool is essential for: (1) computation of geodesic paths using either shooting or path-straightening method, (2) transferring deformations across objects, and (3) modeling of statistical variability in shapes. Using the square-root normal field (SRNF) representation of parameterized surfaces, we present a method for transporting deformations along paths in the shape space. This is difficult despite the underlying space being a vector space because the chosen (elastic) Riemannian metric is non-standard. Using a finite-basis for representing SRNFs of shapes, we derive expressions for Christoffel symbols that enable parallel transports. We demonstrate this framework using examples from shape analysis of parameterized spherical surfaces, in the three contexts mentioned above.
Cite
Text
Xie et al. "Parallel Transport of Deformations in Shape Space of Elastic Surfaces." International Conference on Computer Vision, 2013. doi:10.1109/ICCV.2013.112Markdown
[Xie et al. "Parallel Transport of Deformations in Shape Space of Elastic Surfaces." International Conference on Computer Vision, 2013.](https://mlanthology.org/iccv/2013/xie2013iccv-parallel/) doi:10.1109/ICCV.2013.112BibTeX
@inproceedings{xie2013iccv-parallel,
title = {{Parallel Transport of Deformations in Shape Space of Elastic Surfaces}},
author = {Xie, Qian and Kurtek, Sebastian and Le, Huiling and Srivastava, Anuj},
booktitle = {International Conference on Computer Vision},
year = {2013},
doi = {10.1109/ICCV.2013.112},
url = {https://mlanthology.org/iccv/2013/xie2013iccv-parallel/}
}