"Which country has the sharpest jawlines?" "Where are the biggest eyes?" This report tries to answer questions like these with measured numbers rather than impressions or stereotypes. To build its country-matching engine, Hogamdo collected 100,521 public figure images across 139 countries and measured six core facial metrics using MediaPipe's 478 face landmarks, aggregating them into per-country averages. This article is the first public release of what that dataset shows.
What we measured, and how
The measurement pipeline has three stages. First, we collected publicly available images of actors, athletes, politicians and other public figures for each country (roughly 720 images per country on average). Second, we filtered for front-facing, single-face, adequately sized images, producing a balanced measurement sample of 4,815 faces across countries and genders. Finally, we extracted 478 landmarks from each face with MediaPipe FaceLandmarker and computed six metrics, averaged per country:
- faceRatio โ face length รท face width (higher = longer, slimmer face)
- eyeSize โ eye size relative to face size
- jawSharpness โ how defined the jawline is (higher = closer to a V-line)
- faceSymmetry โ left-right symmetry score (1.0 = perfect symmetry)
- noseRatio โ nose size relative to the face
- lipFullness โ lip thickness relative to the face
All six metrics at a glance โ global averages and extremes
| Metric | Global mean | Highest | Lowest | Korea (of 139) |
|---|---|---|---|---|
| Face length/width ratio | 1.225 | Samoa 1.317 | Zimbabwe 1.157 | 1.251 ยท #23 |
| Eye size | 0.248 | Slovenia 0.298 | Norway 0.216 | 0.252 ยท #51 |
| Jaw sharpness | 1.235 | China 1.292 | Fiji 1.206 | 1.273 ยท #2 |
| Face symmetry | 0.885 | Slovenia 0.909 | Honduras 0.857 | 0.870 ยท #133 |
| Nose ratio | 0.223 | Mongolia 0.241 | Uganda 0.196 | 0.227 ยท #47 |
| Lip fullness | 0.125 | South Africa 0.174 | Iceland 0.096 | 0.125 ยท #52 |
Data: Hogamdo internal dataset โ 100,521 public face images across 139 countries (as of July 2026)
One thing jumps out of the table immediately: South Korea sits mid-pack on most metrics, but ranks #2 out of 139 countries for jaw sharpness โ and #133 for facial symmetry. Let's look closer.
Jaw sharpness: East Asia dominates, Korea is #2 worldwide
The top 10 countries by jaw sharpness show a striking pattern. China (#1), South Korea (#2), Hong Kong (#3), Taiwan (#5) and Japan (#10) โ all five East Asian regions in our dataset made the top 10. The remaining spots went to East African countries: Zambia, Tanzania, Kenya.
Data: Hogamdo internal dataset โ per-country averages from 100,521 public face images across 139 countries (as of July 2026)
The K-beauty association with the "V-line" jaw turns out to be visible in measurement data, not just marketing. Notably, this is unlikely to be purely an effect of cosmetic surgery or makeup: the sample spans a broad range of public figures, yet East Asian jaw sharpness is consistently elevated โ pointing to underlying skeletal structure as the driver.
Eye size: the rankings defy expectations
The top 10 for relative eye size breaks stereotypes. Slovenia is #1, Zimbabwe #2 โ and Japan #3. Contrary to the "Westerners have big eyes" clichรฉ, Norway ranks dead last of 139 countries, with Portugal near the bottom.
Data: Hogamdo internal dataset โ per-country averages from 100,521 public face images across 139 countries (as of July 2026)
The key is that this metric measures eye size relative to the face. A smaller face with proportionally large eyes scores high, while larger skulls with deep-set eyes โ a common Northern European pattern โ measure low. It's a good illustration that "looking big-eyed" and measured proportion are different things.
Lip fullness: the metric with the biggest regional differences
Of the six metrics, lip fullness varies the most across regions. Africa (0.143) measures fullest and North America (0.109) and Eastern Europe (0.110) thinnest โ a gap of about 31%. By contrast, face symmetry is essentially flat across every region at around 0.88.
Data: Hogamdo internal dataset โ per-country averages from 100,521 public face images across 139 countries (as of July 2026)
Latin America (0.132) and Southeast Asia (0.128) follow Africa, while East Asia (0.116) measures exactly level with Western Europe (0.116). The stereotype that East Asian lips are comparatively thin doesn't hold โ at least not against Western Europe.
Symmetry: humanity looks more alike than you'd think
This may be the least flashy finding, but perhaps the most important one. The average facial symmetry scores of all 139 countries cluster in the narrow band of 0.857โ0.909, with a standard deviation of just 0.010 โ the smallest between-country variation of any metric. Whatever the country, human faces average around 12% left-right asymmetry.
We take a deeper look at the symmetry distribution โ and test the "symmetry equals beauty" claim โ in a separate article: Symmetry Score Distribution Analysis.
Limitations โ how to read this data honestly
Full disclosure: this dataset has three clear limitations. First, sample bias. It is built from public figures โ actors, athletes, officials โ so it reflects the average of "faces that appear in media," not the average citizen of each country. Second, sample size per country is modest (dozens of measured faces per country), so third-decimal differences between individual countries are not statistically meaningful; regional patterns matter more than exact ranks. Third, the tyranny of averages: a national mean of 1.25 does not mean most people there measure 1.25 โ within-country variation is far larger than between-country variation.
The data is still worth publishing because most discussion of facial features across cultures runs on impressions and stereotypes. A single measurement pipeline applied uniformly to 139 countries gives that conversation a minimal factual baseline. How Hogamdo's country matching actually uses this dataset is described on our methodology page.
๐ References
- โข Hogamdo internal dataset (2026). 100,521 public figure images across 139 countries; 4,815 measured samples aggregated to country-level averages.
- โข Lugaresi, C. et al. (2019). MediaPipe: A Framework for Building Perception Pipelines. arXiv:1906.08172.
- โข Kartynnik, Y. et al. (2019). Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs. arXiv:1907.06724.