Statistical Shape Analysis of Human Bodies
Morphological analysis of the human body is crucial for various applications in ergonomics and product design, with significant economic and commercial implications. This paper presents a novel exploration of statistical methods for the analysis of human body shapes based on 3D landmark data. It foc...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO) |
| Repositorio: | r-FISABIO. Repositorio Institucional de Producción Científica |
| OAI Identifier: | oai:dnet:r-fisabio___::a8aece0466de0d597e099e36d1a15930 |
| Acceso en línea: | https://fisabio.portalinvestigacion.com/publicaciones/21022 |
| Access Level: | acceso abierto |
| Palabra clave: | anthropometry principal component analysis Riemannian manifold statistical shape analysis |
| Sumario: | Morphological analysis of the human body is crucial for various applications in ergonomics and product design, with significant economic and commercial implications. This paper presents a novel exploration of statistical methods for the analysis of human body shapes based on 3D landmark data. It focuses on the application of well-established statistical methods within the framework of Kendall's 3D shape space. It is well known that Kendall's 3D shape space has non-constant curvature at all points. A key contribution of this study is the detailed examination of the curvature of Kendall's space at points corresponding to human body shapes, highlighting its implications for posterior statistical analysis. A study of the distances in the dataset is also carried out. From this point, we also compare the performance of intrinsic (Riemannian) methods and Euclidean approximations for mean shape estimation, group difference identification, and dimensionality reduction, providing a comprehensive assessment of their respective strengths and limitations in these contexts. These findings aim to improve the statistical understanding of body morphology and provide valuable guidance for applications in fields such as product design and ergonomics. |
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