Abstract
This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.
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Acknowledgments
This work was supported by the Research Foundation in Flanders (FWO SB) and the VLAIO PLATO-project. The authors would like to thank Vigo nv, More Institute vzw and Orfit Industries nv for their continued contribution to the project.
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Van Houtte, J. et al. (2019). An Articulating Statistical Shape Model of the Human Hand. In: Cassenti, D. (eds) Advances in Human Factors in Simulation and Modeling. AHFE 2018. Advances in Intelligent Systems and Computing, vol 780. Springer, Cham. https://doi.org/10.1007/978-3-319-94223-0_41
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DOI: https://doi.org/10.1007/978-3-319-94223-0_41
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