Geometric morphometry serves biologists and anthropologists to rigorously and quantitatively describe shapes. These representations can be treated as a statistical sample, allowing the researchers to study its variability within groups and correlate it to other features. Geometric morphometry uses landmarks as the proxy for shape, with consistent semantics in each specimen. General triangle meshes do not have this property, and as such, semantically consistent remeshes must be created artificially. This thesis deals with the design of an algorithm that consistently resamples a set of surface models for the purpose of statistical analysis. Coherent point drift was employed to perform nonrigid registration, whose result is then used to generate a semantically consistent remeshes. This approach was successfully applied in a number of studies. As CPD is compute-intensive, we propose methods of accelerating both its initialization and processing phases. Also, an extension was introduced, that can map the deviation of the surfaces from perfect bilateral symmetry and analyze it in a sample, which is significant, among others, for quantification of pathologies. Manual trimming of the surfaces and merging datasets results in outlier regions in the individual surfaces and potentially large differences in their vertex...
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:437017 |
| Date | January 2020 |
| Creators | Dupej, Ján |
| Contributors | Pelikán, Josef, Telea, Alexandru C., Váša, Libor |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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