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DC Field | Value | Language |
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dc.contributor.author | Bauer, M | - |
dc.contributor.author | Bruveris, M | - |
dc.contributor.author | Harms, P | - |
dc.contributor.author | Møller-Andersen, J | - |
dc.date.accessioned | 2016-06-16T11:29:22Z | - |
dc.date.available | 2016-06-16T11:29:22Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | arXiv:1603.03480v2 | en_US |
dc.identifier.uri | http://arxiv.org/abs/1603.03480v2 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/12804 | - |
dc.description.abstract | Statistical shape analysis can be done in a Riemannian framework by endowing the set of shapes with a Riemannian metric. Sobolev metrics of order two and higher on shape spaces of parametrized or unparametrized curves have several desirable properties not present in lower order metrics, but their discretization is still largely missing. In this paper, we present algorithms to numerically solve the geodesic initial and boundary value problems for these metrics. The combination of these algorithms enables one to compute Karcher means in a Riemannian gradient-based optimization scheme and perform principal component analysis and clustering. Our framework is sufficiently general to be applicable to a wide class of metrics. We demonstrate the effectiveness of our approach by analyzing a collection of shapes representing HeLa cell nuclei. | en_US |
dc.description.sponsorship | All authors were partially supported by the Erwin Schr odinger Institute programme: In nite-Dimensional Riemannian Geometry with Applications to Image Matching and Shape Analysis. M. Bruveris was supported by the BRIEF award from Brunel University London. M. Bauer was supported by the FWF project \Geometry of shape spaces and related in nite dimensional spaces" (P246251) | en_US |
dc.language.iso | en | en_US |
dc.publisher | ArXiv | en_US |
dc.subject | Shape analysis | en_US |
dc.subject | Shape registration | en_US |
dc.subject | Sobolev metric | en_US |
dc.subject | Geodesics | en_US |
dc.subject | Karcher mean | en_US |
dc.subject | B-splines | en_US |
dc.title | A numerical framework for sobolev metrics on the space of curves | en_US |
dc.type | Article | en_US |
pubs.notes | 25 pages, 14 figures | - |
Appears in Collections: | Dept of Mathematics Research Papers |
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Fulltext.pdf | 1.47 MB | Adobe PDF | View/Open |
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