Unknown

Dataset Information

0

Landmark-free geometric methods in biological shape analysis.


ABSTRACT: In this paper, we propose a new approach for computing a distance between two shapes embedded in three-dimensional space. We take as input a pair of triangulated genus zero surfaces that are topologically equivalent to spheres with no holes or handles, and construct a discrete conformal map f between the surfaces. The conformal map is chosen to minimize a symmetric deformation energy Esd(f) which we introduce. This measures the distance of f from an isometry, i.e. a non-distorting correspondence. We show that the energy of the minimizing map gives a well-behaved metric on the space of genus zero surfaces. In contrast to most methods in this field, our approach does not rely on any assignment of landmarks on the two surfaces. We illustrate applications of our approach to geometric morphometrics using three datasets representing the bones and teeth of primates. Experiments on these datasets show that our approach performs remarkably well both in shape recognition and in identifying evolutionary patterns, with success rates similar to, and in some cases better than, those obtained by expert observers.

SUBMITTER: Koehl P 

PROVIDER: S-EPMC4707851 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Landmark-free geometric methods in biological shape analysis.

Koehl Patrice P   Hass Joel J  

Journal of the Royal Society, Interface 20151201 113


In this paper, we propose a new approach for computing a distance between two shapes embedded in three-dimensional space. We take as input a pair of triangulated genus zero surfaces that are topologically equivalent to spheres with no holes or handles, and construct a discrete conformal map f between the surfaces. The conformal map is chosen to minimize a symmetric deformation energy Esd(f) which we introduce. This measures the distance of f from an isometry, i.e. a non-distorting correspondence  ...[more]

Similar Datasets

| S-EPMC4783062 | biostudies-literature
| S-EPMC5608350 | biostudies-literature
| S-EPMC8830334 | biostudies-literature
| S-EPMC10582673 | biostudies-literature
| S-EPMC7814138 | biostudies-literature
| S-EPMC6110727 | biostudies-literature
| S-EPMC8864294 | biostudies-literature
| S-EPMC7880197 | biostudies-literature
| S-EPMC5789073 | biostudies-literature
| S-EPMC3842927 | biostudies-literature