UCT CS Research Document Archive

Comparing the accuracy and precision of three techniques for estimating missing landmarks when reconstructing fossil hominin crania

Neeser, Rudolph, Rebecca Rogers Ackermann and James Gain (2009) Comparing the accuracy and precision of three techniques for estimating missing landmarks when reconstructing fossil hominin crania. American Journal of Physical Anthropology 140(1):1-18.

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Abstract

Various methodological approaches have been used for reconstructing fossil hominin remains in order to increase the sample sizes and the better understand morphological variation. Among these, morphometric quantitative techniques for reconstruction are increasingly common. Here we compare the accuracy of three approaches—mean substitution, thin plate splines, and multiple linear regression—for estimating missing landmarks of damaged fossil specimens. Comparisons are made varying the number of missing landmarks, sample sizes, and the reference species of the population used to perform the estimation. The testing is performed on landmark data from individuals of Homo sapiens, Pan troglodytes and Gorilla gorilla, and nine hominin fossil specimens. Results suggest that when a small, same-species fossil reference sample is available to guide reconstructions, thin plate spline approaches perform best. However, if no such sample is available (or if the species of the damaged individual is uncertain), estimates of missing morphology based on a single individual (or even a small sample) of close taxonomic affinity are less accurate than those based on a large sample of individuals drawn from more distantly related extant populations using a technique (such as a regression method) able to leverage the information (e.g., variation/covariation patterning) contained in this large sample. Thin plate splines also show an unexpectedly large amount of error in estimating landmarks, especially over large areas. Recommendations are made for estimating missing landmarks under various scenarios.

EPrint Type:Journal (Paginated)
Keywords:landmarks; estimation; mean substitution; thin plate splines; regression
Subjects:I Computing Methodologies: I.3 COMPUTER GRAPHICS
J Computer Applications: J.2 PHYSICAL SCIENCES AND ENGINEERING
I Computing Methodologies: I.6 SIMULATION AND MODELING
ID Code:568
Deposited By:Gain, James
Deposited On:30 November 2009