Methodology
We transparently document the technical principles and data-building process behind Hogamdo's face analysis results
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🧰 Core Technology Stack
Hogamdo relies on the following proven open-source and official AI models:
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Google MediaPipe Face LandmarkerAn open-source face landmark detection framework released by Google. It extracts 478 3D facial points in real time. 공식 문서 →
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ArcFace (DeepFace 라이브러리)A deep learning model that converts a face into a 512-dimensional vector (embedding) to measure similarity. It is one of the industry-standard face recognition models in wide use. DeepFace GitHub →
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In-house Scoring AlgorithmCombines 11 facial metrics (face ratio, eye size, cheekbones, lips, jawline, etc.) with per-country embedding data to compute affinity scores for 139 countries.
⚙️ Analysis Pipeline
MediaPipe detects the face in the uploaded photo and extracts 478 3D landmark coordinates (x, y, z). This step runs locally in your browser, so the original image is never sent to our servers.
From the landmark coordinates we compute 11 facial-ratio metrics: face aspect ratio, eye-size ratio, inter-eye distance, nose ratio, lip thickness, jawline angle, cheekbone width, facial symmetry, and more.
The 512-dimensional embedding vector extracted by ArcFace is compared against each country's pre-built average embedding using cosine similarity.
Metric similarity and embedding similarity are combined as a weighted average to compute an affinity score (0-100) for each of the 139 countries. Countries within the same region receive additional calibration so regional characteristics are reflected.
📐 Facial Metrics Glossary
Definitions of the six core metrics used in the analysis results and statistics pages. All values are ratios computed from landmark coordinates and represent relative proportions within the face, not absolute sizes.
The ratio of face height to width. Higher values mean a longer face, lower values a rounder one.
The area of the eyes relative to the whole face. Higher values mean the eyes occupy a larger share of the face.
How sharply defined and angular the jawline contour is. Higher values mean a more defined outline.
How symmetric the left and right facial landmarks are, measured from 0 to 1. Closer to 1 means more symmetric.
Nose size relative to the face, derived from nose length and width combined.
Lip thickness relative to the face. Higher values mean fuller lips.
🌐 Data Coverage
Hogamdo's per-country average-metric dataset is currently built at the following scale. All figures are aggregated averages and do not identify any individual.
📊 Data Sources
The per-country facial-feature database was built from the following public datasets and sources:
- Facial anthropometric data from public demographic and anthropological literature
- Average embeddings aggregated from public face-image datasets for each country (individuals not identifiable)
- Public research and survey data on aesthetic preferences in each cultural region
The data is aggregate information representing each country's 'average characteristics' rather than any specific individual's face, and is improved and updated regularly.
⚠️ Limitations and Caveats
To help you interpret Hogamdo's analysis results correctly, we state the following limitations:
- 'Affinity' is a reference indicator based on each country's 'average tendency' and does not represent any individual's actual preference.
- Standards of beauty are subjective and change with era and culture. This service is provided as entertainment reference material, not a scientific verdict.
- Shooting conditions such as lighting, angle, expression, and resolution can affect the analysis results.
- It must not be used as grounds to interpret any ethnicity, country, or appearance as superior or inferior.
📜 Algorithm Changelog
지역별 편향 튜닝 완료 — 8개 지역 전체에서 이상치 편차 15.2pp까지 축소
ArcFace 임베딩 도입으로 기하학 메트릭 단독 방식 대비 정확도 향상
MediaPipe Face Landmarker 기반 초기 모델 출시 (139개국)