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Three-dimensional (3D) trapezium models from Homo sapiens, Gorilla gorilla, Pan troglodytes, Australopithecus afarensis (A.L.333-80), and Homo habilis (O.H.7-NNQ) were acquired through laser digitizing. Least-square planes were generated for each articular surface, and the angles between the planes were compared. Each extant species displays an overall pattern that distinguishes it from the others. The observed angles in G. gorilla and P. troglodytes are more similar to one other than either is to H. sapiens. Our results, obtained from using new 3D modeling and analytical tools, raise interesting questions about the functional capabilities of the fossil trapezia. Multivariate statistical analyses indicate that A.L.333-80 is morphologically more similar to that of modern humans, whereas the O.H.7 trapezium is more similar to that of the gorilla. Significant differences between A.L.333-80 and the extant species occur, but some similarities to humans suggest the ability to form the distinctively human forceful pad-to-side and three-jaw chuck grips. Some key morphological differences from humans highlighted and quantified by our research suggest limitations in the functional capabilities of the O.H.7 trapezium, particularly in those that facilitate pronation at the base of the second metacarpal. If the O.H.7 trapezium represents part of the hand responsible for manufacturing and using the stone tools found at Olduvai, our results suggest that the hand manipulated the stones in a way for which we have no modern analog. Alternative considerations are that the O.H.7 trapezium is not representative of other trapezia from its species (i.e., N ϭ 1), or that it represents another primate or hominid species. Am J Phys

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Automatically generating 3D building models from 2D architectural drawings has many useful applications in the architecture engineering and construction community. This survey of model generation from paper and CAD-based architectural drawings covers the common pipeline and compares various algorithms for each step of the process.

In this paper we present dart throwing algorithms to generate maximal Poisson disk point sets directly on 3D surfaces. We optimize dart throwing by efficiently excluding areas of the domain that are already covered by existing darts. In the case of triangle meshes, our algorithm shows dramatic speed improvement over comparable sampling methods. The simplicity of our basic algorithm naturally extends to the sampling of other surface types, including spheres, NURBS, subdivision surfaces, and implicits. We further extend the method to handle variable density points, and the placement of arbitrary ellipsoids without overlap. Finally, we demonstrate how to adapt our algorithm to work with geodesic instead of Euclidean distance. Applications for our method include fur modeling, the placement of mosaic tiles and polygon remeshing.