Statistical Frameworks for Mapping 3D Shape Variation onto Genotypic and Phenotypic Variation

The recent curation of large-scale databases with 3D surface scans of shapes has motivated the development of tools that better detect global-patterns in morphological variation. Studies which focus on identifying differences between shapes have been limited to simple pairwise comparisons and rely on pre-specified landmarks (that are often known). In this talk, we present SINATRA: a statistical pipeline for analyzing collections of shapes without requiring any correspondences. Our method takes in two classes of shapes and highlights the physical features that best describe the variation between them.

[Slides]

日期：

2020年3月5日

演讲者：

Lorin Crawford

所属机构：

Brown University