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Symmetry 2018, 10(7), 263; https://doi.org/10.3390/sym10070263

A Survey of Methods for Symmetry Detection on 3D High Point Density Models in Biomedicine

Department of Industrial Engineering, University of Florence, 50139 Florence, Italy
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Received: 4 May 2018 / Revised: 28 June 2018 / Accepted: 4 July 2018 / Published: 4 July 2018
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Abstract

Versatile, cheap and non-invasive 3D acquisition techniques have received attention and interest in the field of biomedicine in recent years as the accuracy of developed devices permits the acquisition of human body shapes in detail. Interest in these technologies derives from the fact that they have the potential to overcome some limitations of invasive techniques (CT, X-rays, etc.) and those based on 2D photographs for the acquisition of 3D geometry. However, the data acquired from the 3D scanner cannot be directly used but need to be processed as they consist of 3D coordinates of the acquired points. Therefore, many researchers have proposed different algorithms which recognise the shape of human body and/or its features when starting from a 3D point cloud. Among all possible human body features to be evaluated, symmetry results the most relevant one. Accordingly, this survey systematically investigates the methods proposed in the literature to recognise 2D symmetry by the symmetry line and bilateral symmetry by the symmetry plane. The paper also analyses qualitative comparisons among the proposed methods to provide a guide for both practitioners and researchers. View Full-Text
Keywords: symmetry line; symmetry plane; 3D scan; digital human model symmetry line; symmetry plane; 3D scan; digital human model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Bartalucci, C.; Furferi, R.; Governi, L.; Volpe, Y. A Survey of Methods for Symmetry Detection on 3D High Point Density Models in Biomedicine. Symmetry 2018, 10, 263.

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