2018/07/31 by Tingran Gao, Shahar Z. Kovalsky, Gao, Tingran +6
Mathematics · Social Sciences · #Morphological variations and asymmetry #Pleistocene-Era Hominins and Archaeology #acm:60G15 #acm:62K05 #acm:65D18 #msc:60G15 #msc:62K05 #msc:65D18 #stat.AP
paper · pdf · doi:10.48550/arxiv.1807.11887
41 pages, 17 figures, 3 tables. Some portions of this work appeared earlier as arXiv:1802.03479, which was split into 2 parts during the refereeing process. This version combines the main text with the supplemental materials. Figure sizes have been reduced to meet arxiv size limit
arxiv created 2019/01/08 · arxiv updated 2019/01/10
We demonstrate applications of the Gaussian process-based landmarking algorithm proposed in [T. Gao, S.Z. Kovalsky, and I. Daubechies, SIAM Journal on Mathematics of Data Science (2019)] to geometric morphometrics, a branch of evolutionary biology centered at the analysis and comparisons of anatomical shapes, and compares the automatically sampled landmarks with the "ground truth" landmarks manually placed by evolutionary anthropologists; the results suggest that Gaussian process landmarks perform equally well or better, in terms of both spatial coverage and downstream statistical analysis. We provide a detailed exposition of numerical procedures and feature filtering algorithms for computing high-quality and semantically meaningful diffeomorphisms between disk-type anatomical surfaces.