A Comparison of Semilandmarking Approaches in the Analysis of Size and Shape

Abstract

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.

Normal human craniofacial growth and development from 0 to 4 years

“…This is, by now, the standard approach in morphometric studies of skeletal form 61 . Our newly published experiments 60 , 64 indicate that it achieves similar results to those from the non-iterative closest points (NICP) method for point cloud registration 65 , commonly applied in computer vision. However, neither approach can ensure homology of SLMs 66 , 67 .…”

A computerized facial approximation method for Homo sapiens based on facial soft tissue thickness depths and geometric morphometrics

“…In morphometrics, sliding approaches by minimizing Procrustes distance or bending energy (Gunz & Mitteroecker, 2013 ) have been developed to project semilandmarks of the template to each specimen based on equivalent landmarks. The present study used the hybrid nonrigid registration approach which can yield consistent morphometric results (Shui et al, 2023 ) to identify high‐density semilandmarks. Furthermore, the constant orientation, that is, normal vector of every landmark and semilandmark of the average skull, is treated as the measured direction across samples and can approximate dense points on the facial envelope.…”

“…In morphometrics, semilandmarks determined by algorithms have increasingly been applied to capture detailed morphology. The choice of landmark and semilandmark configuration affects the morphometric analysis and visualization (Shui et al, 2023 ). This study is limited in its scope, having examined landmarks alone and landmarks and high‐density semilandmarks together to explore nose (or mouth) covariations between hard and soft tissues and to predict soft tissue shapes.…”

Do astigmatid teeth matter: a tribological review of cheliceral chelae in co-occuring mites from UK beehives

“…Novel features are not straightforward to deal with on jaws (Gómez-Robles et al 2011). A degree of post hoc trial and error and choice by the analyst including semi-landmark density would be needed to reconstruct imaginary profiles parsimoniously (see Shui et al 2023).…”