East Asian facial features
How a face with East Asian ancestry scores across 17 structural metrics. Descriptive anthropometry, not a hierarchy.
Beauty is multi-ethnic. Published cross-cultural research finds no single ethnicity scores higher in aggregate. This page describes the metric distribution, not a ranking.
17 metrics · Farkas international norms · Free · No signup
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Why most face tools mis-score East Asian faces
Most legacy face-scoring tools were calibrated on Caucasian-dominant datasets, which means the eye aspect ratio, nasal index, and midface projection thresholds were set against one population's distribution. When a monolid or folded East Asian eye is scored against a Caucasian eye-aperture norm, the resulting percentile reads as a low score on a metric where the face is actually average for its population. Choe et al. (2004) on Korean craniofacial norms and Le et al. (2002) on Vietnamese norms both document distributions that diverge meaningfully from Western reference datasets on a handful of specific metrics.
Our score does not split by ancestry. Every metric is placed against one reference group, everyone who has scanned here, and the Face Score is checked against a human-rated benchmark of mostly young, mostly East Asian faces. So this page puts the published norms next to your numbers (Farkas international atlas plus Korean and Japanese datasets where validated norms exist): a metric that reads low against our pooled group can still sit at the average for your population.
The 17 structural metrics themselves are universal geometry. Facial thirds, fifths, FWHR, canthal tilt, jawline ratio, and the rest are defined the same way regardless of population. What changes is the reference group a reading is compared against. Ours is one pooled group, everyone who has scanned here; the published East Asian norms on this page are the context for reading it.
5 structural patterns documented in East Asian craniofacial research
Bizygomatic to bigonial ratio
Korean and Japanese norms (Choe 2004; Wang et al. 2011) document a tendency toward a wider bizygomatic relative to bigonial measurement compared to European norms, contributing to the perception of higher cheekbones. Wide individual variance.
Midface projection
International atlases (Farkas et al. 2005) record slightly flatter midface projection on average in East Asian populations compared to European samples. Descriptive, not evaluative; published norms treat both flatter and projected as normal variation.
Nasal index
Nasal width to nasal height ratio sits in a distinct sub-range. Published norms treat this as the population mean, not a deviation from a Caucasian norm.
Eye aperture geometry
Monolid and double-lid eyes register slightly different eye aspect ratios. Published norms (Choe 2004) show the Caucasian eye-aperture mean is not a universal target.
Lower-face proportion
Average lower-face height relative to total facial height clusters slightly shorter in published East Asian norms vs European samples. Carried as descriptive context in the metric layer.
Hair and brow line
Darker, denser eyebrow hair and a typically lower hairline shift how the brow-to-eye distance metric reads compared to lighter-brow populations. The score treats this as structural signal rather than as a styling artifact.
Why one pooled score needs published norms beside it
A single composite forces a face into one reference distribution. On many tools that distribution is implicitly Caucasian because the underlying training data was. Ours is one pooled group, everyone who has scanned here, and the Face Score's benchmark is mostly young, mostly East Asian. We do not compute a separate percentile for East Asian faces, so a reading that differs from the pooled middle can still be the average for your population.
Our percentile answers one question: where do you sit relative to the people who scanned here? The published norms on this page answer another: where do faces with similar ancestry usually sit? Both are descriptive. Neither is a verdict. Where they disagree, the published norm is usually the better guide to what is typical for your face.
Honest limits of any ethnicity-aware face score
- Ancestry is a continuum. Mixed-ancestry faces do not cleanly belong to a single distribution, and published single-population norms are least useful in that case. Our pooled score is not split by ancestry, so it reads the same way for everyone.
- Published norms (Farkas 2005, Choe 2004, Le 2002, Wang 2011) sample a small number of subgroups within each population label. East Asian as a category covers Korean, Japanese, Han Chinese, Vietnamese, and many other populations with distinct craniofacial distributions. Treat any published population norm as directional, not as a precise read.
- The composite measures still photography. In-person impressions involve motion, voice, and posture none of which a photo captures. A high composite does not guarantee in-person impact and a low composite does not preclude it.
- The score does not, and should not, recommend interventions targeting ethnic features. Eyelid surgery, midface implants, and similar procedures carry surgical risk and rarely move the underlying composite by more than a few points relative to their cost. The recommendation layer in the report targets soft-tissue and grooming levers that work across populations.
- Beauty is multi-ethnic. The published cross-cultural preference research is unambiguous on this. Any tool that claims one population scores higher than another in aggregate is wrong about the underlying research.
East Asian facial features FAQ
Does this page rank East Asian faces against other ethnicities?+
Which structural metrics tend to differ in East Asian faces?+
Are the percentiles compared to East Asian norms or universal norms?+
Does the test handle epicanthic folds and monolids correctly?+
Is the test biased toward Western beauty standards?+
Is my photo uploaded?+
What does the free score include and what does the $14.99 report add?+
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17 metrics · Farkas international norms · Photos auto-deleted
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