面部复杂性的机器学习驱动解码:用于正面面部分析的钻石和三角形几何
Peiqi Wang1, Heng Zeng2, Runyu Ma1
1State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China; Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
概括
使用钻石和三角形几何学的新机器学习模型分析了跨种族的面部吸引力. 它确定了面部和的关键比例,有助于跨种族分析和个性化治疗.
科学领域:
- 审美学 在审美学方面
- 计算机科学 计算机科学
- 人类学是人类学.
背景情况:
- 传统的数学定律不能充分反映面部的复杂性和变异性.
- 需要一个全面的,种族间可比的系统来进行正面面部面部分析.
- 面部吸引力受到复杂的几何比例的影响.
研究的目的:
- 开发一种机器学习模型,用于分析不同种族的面部吸引力.
- 用一个钻石和三角形的几何框架来解码审美决定的面部特征.
- 量化一个面孔符合普遍接受的吸引力标准的概率.
主要方法:
- 对高加索和亚洲女性面部的形态分析 (有吸引力与普通).
- 基于钻石和三角形几何框架的机器学习模型的开发.
- 使用21个面部比例指数,从几何学中导出,作为支持向量机 (SVM) 模型的输入.
主要成果:
- SVM模型在区分有吸引力的和普通的面孔方面表现出卓越的有效性.
- 具有吸引力的面孔,跨越种族,优先考虑面部高度与面部中部宽度和外侧口腔距离的比例协调.
- 其他比例指数的等级重要性中观察到特定于种族的变化.
结论:
- 钻石和三角形的几何框架有效地区分了吸引人的普通面孔,具有跨民族的相似之处.
- 机器学习模型为跨民族面部分析提供了有价值的工具.
- 这种方法为面部美容的定制治疗计划提供了参考.
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