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A data-driven classification of 3D foot types by archetypal shapes based on landmarks

机译:基于地标的原型形状数据驱动3D脚型类型的分类

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摘要

The taxonomy of foot shapes or other parts of the body is important, especially for design purposes. We propose a methodology based on archetypoid analysis (ADA) that overcomes the weaknesses of previous methodologies used to establish typologies. ADA is an objective, data-driven methodology that seeks extreme patterns, the archetypal profiles in the data. ADA also explains the data as percentages of the archetypal patterns, which makes this technique understandable and accessible even for non-experts. Clustering techniques are usually considered for establishing taxonomies, but we will show that finding the purest or most extreme patterns is more appropriate than using the central points returned by clustering techniques. We apply the methodology to an anthropometric database of 775 3D right foot scans representing the Spanish adult female and male population for footwear design. Each foot is described by a 5626 × 3 configuration matrix of landmarks. No multivariate features are used for establishing the taxonomy, but all the information gathered from the 3D scanning is employed. We use ADA for shapes described by landmarks. Women's and men's feet are analyzed separately. We have analyzed 3 archetypal feet for both men and women. These archetypal feet could not have been recovered using multivariate techniques.
机译:脚形状或身体其他部位的分类很重要,特别是对于设计目的。我们提出了一种基于原型分析(ADA)的方法,该方法克服了先前方法用来建立类型的方法的弱点。 ADA是一种目标,数据驱动方法,用于寻求极端模式,数据中的原型模式。 ADA还将数据解释为原型模式的百分比,这使得这种技术即使对于非专家而言也可以理解和可访问。通常考虑聚类技术用于建立分类,但我们将显示发现最纯粹或最极端的模式比使用聚类技术返回的中心点更适合。我们将该方法应用于代表西班牙成年女性和男性人口的775 3D右脚扫描的人类测量数据库。每只脚由5626×3配置矩阵描述的地标。没有使用多变量特征来建立分类物,但是采用了从3D扫描收集的所有信息。我们使用地标描述的ADA形状。妇女和男士的脚分别分析。我们为男女分析了3个原型脚。这些原型脚不可能使用多变量技术来恢复。

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