1. Spatial Computing & Facial Landmark Detection
Aesthetic diagnostics begin with coordinate mapping. Computer vision algorithms isolate facial regions and extract a grid of 68 spatial coordinate landmarks. These coordinates define structural proportions, skeletal symmetry, and volumetric ratios.
By calculating distance ratios between the pupils (interpupillary distance), maxilla width, nose height, and mandibular angle, the software evaluates proportion indexes. This math maps out facial metrics, indicating which regions can be enhanced via localized toning or posture correction.
2. Epidermal Surface & Texture Metrics
Beyond skeletal landmarks, the analyzer maps skin layers. The computer vision engine evaluates light reflection and micro-contrast:
- Gloss Mapping (Sebum Index): High light reflection in the T-zone indicates elevated sebum output.
- Micro-contrast (Dehydration Index): Fine dry lines and scaling increase edge-detection contrast, highlighting dehydration layers.
- Pigment Uniformity (Hyperpigmentation Index): Variations in color indicate melanin accumulation or UV degradation.
3. Closed-Loop Progress Calculations
A single scan only shows a snapshot. The value of AI face scanning is in the comparison loop. Every 7 days, comparative diagnostics check changes against the baseline. If skin texture improves, the algorithm increments active ingredient concentration; if facial puffiness drops, fitness cardios adjust to keep progress steady.