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Published on: November 6, 2014
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Principal component analysis of three-dimensional face shape: Identifying shape features that change with age
1Skin Research Department, POLA Chemical Industries, Inc., Totsuka-ku, Yokohama, Japan.
Summary
Facial shape analysis reveals age-related changes like reduced upper face volume and increased cheek/chin volume. Principal component analysis effectively identifies these distinct age-related facial features.
Area of Science:
- Aesthetics
- Anthropometry
- Gerontology
Background:
- Limited understanding of comprehensive facial shape features.
- Previous studies focused on individual aging signs like wrinkles.
- Need for quantitative analysis of age-related facial shape changes.
Purpose of the Study:
- Quantitatively measure facial shape differences.
- Investigate age-related changes in facial shape features.
- Identify shape features characteristic of different age groups.
Main Methods:
- Three-dimensional facial analysis of 280 Japanese women (20-69 years).
- Principal Component Analysis (PCA) to define individual shape features.
- Evaluation of feature-age relationships.
Main Results:
- Middle age: decreased upper face volume, increased cheek/chin volume.
- Older age: increased lower cheek/chin volume, sagging skin, jaw distortion.
- PCA effectively identified age-specific facial shape characteristics.
Conclusions:
- PCA is effective for identifying individual and age-related facial shape features.
- Method allows straightforward measurement of soft tissue and skeletal changes.
- 3D facial imaging simplifies analysis of age-related facial morphology.
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