Often, few landmarks can be reliably identified in analyses of form variation and covariation. Thus, 'semilandmarking' algorithms have increasingly been applied to surfaces and curves. However, the locations of semilandmarks depend on the investigator's choice of algorithm and their density. In consequence, to the extent that different semilandmarking approaches and densities result in different locations of semilandmarks, they can be expected to yield different results concerning patterns of variation and co-variation. The extent of such differences due to methodology is, as yet, unclear and often ignored. In this study, the performance of three landmark-driven semilandmarking approaches is assessed, using two different surface mesh datasets (ape crania and human heads) with different degrees of variation and complexity, by comparing the results of morphometric analyses. These approaches produce different semilandmark locations, which, in turn, lead to differences in statistical results, although the non-rigid semilandmarking approaches are consistent. Morphometric analyses using semilandmarks must be interpreted with due caution, recognising that error is inevitable and that results are approximations. Further work is needed to investigate the effects of using different landmark and semilandmark templates and to understand the limitations and advantages of different semilandmarking approaches.
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http://dx.doi.org/10.3390/ani13071179 | DOI Listing |
Animals (Basel)
March 2023
Department of Archaeology, University of York, King's Manor, York YO1 7EP, UK.
Often, few landmarks can be reliably identified in analyses of form variation and covariation. Thus, 'semilandmarking' algorithms have increasingly been applied to surfaces and curves. However, the locations of semilandmarks depend on the investigator's choice of algorithm and their density.
View Article and Find Full Text PDFAnimals (Basel)
January 2023
Department of Archaeology, University of York, King's Manor, York YO1 7EP, UK.
In landmark-based analyses of size and shape variation and covariation among biological structures, regions lacking clearly identifiable homologous landmarks are commonly described by semilandmarks. Different algorithms may be used to apply semilandmarks, but little is known about the consequences of analytical results. Here, we assess how different approaches and semilandmarking densities affect the estimates and visualisations of mean and allometrically scaled surfaces.
View Article and Find Full Text PDFAm J Phys Anthropol
May 2021
Department of Pediatrics, University of Washington, Seattle, Washington, USA.
Objectives: Increased use of three-dimensional (3D) imaging data has led to a need for methods capable of capturing rich shape descriptions. Semi-landmarks have been demonstrated to increase shape information but placement in 3D can be time consuming, computationally expensive, or may introduce artifacts. This study implements and compares three strategies to more densely sample a 3D image surface.
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