2021
DOI: 10.48550/arxiv.2105.00678
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A new variational model for shape graph registration with partial matching constraints

Abstract: This paper introduces a new extension of Riemannian elastic curve matching to a general class of geometric structures, which we call (weighted) shape graphs, that allows for shape registration with partial matching constraints and topological inconsistencies. Weighted shape graphs are the union of an arbitrary number of component curves in Euclidean space with potential connectivity constraints between some of their boundary points, together with a weight function defined on each component curve. The framework… Show more

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Cited by 1 publication
(4 citation statements)
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“…A second avenue for future research would be to replace the L 2 or Fisher-Rao penalties by different regularization metrics for the weight change function in either a static or metamorphosis setting, with the purpose of imposing spatially smoother weights. In the special case of rectifiable varifolds, one could for instance introduce higher-order Sobolev or total variation norms of the weight change function, by analogy with what has been considered in the context of functional shapes in [19] or elastic shape analysis in [26].…”
Section: Discussionmentioning
confidence: 99%
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“…A second avenue for future research would be to replace the L 2 or Fisher-Rao penalties by different regularization metrics for the weight change function in either a static or metamorphosis setting, with the purpose of imposing spatially smoother weights. In the special case of rectifiable varifolds, one could for instance introduce higher-order Sobolev or total variation norms of the weight change function, by analogy with what has been considered in the context of functional shapes in [19] or elastic shape analysis in [26].…”
Section: Discussionmentioning
confidence: 99%
“…Through some of the presented simulations, we will show that it can provide robustness to different types of density imbalances in structured and unstructured geometric data. But we shall also illustrate its potential to deal with partially observed data with curves and surfaces, which has been a recurrent and challenging issue for many different shape analysis models [22][23][24][25][26][27].…”
Section: Introductionmentioning
confidence: 99%
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