Skin Analysis

GlamAR’s AI based Facial Skin Analysis brings intelligent skincare diagnostics to any digital experience. Powered by deep learning and computer vision, it evaluates skin health in real time using a single camera capture. It detects over 14 skin conditions, including acne, wrinkles, pigmentation, and pores, and returning annotated, visual results.

The analysis runs entirely through the user’s camera, no wearables or specialized hardware required, which makes it flexible to deploy in web or mobile environments at scale.

This section explains what insights it provides, how Skin Analysis works, and how it integrates into your GlamAR applications

What Insights It Provides?

Metric / Parameter	Tech Name	Category	Value / Range	Annotated Visualization	Description
Skin Score	total_skin_score	Overall Health	Integer (0–100)	✅	Aggregate health evaluation summarizing all measured concerns. Returns a summary of the skin issue and an annotated image showing all identified problems.
Skin Type	skin_type	Classification	Oily / Dry / Normal / Combination	❌	Classifies overall skin behavior based on oil and moisture balance across facial zones.
Skin Tone	skin_tone	Classification	Fair / Light / Medium / Olive / Tan / Deep	❌	Melanin-based tone classification identifying the user's natural skin shade category.
Skin Shade	skin_shade	Classification	Hex color code (e.g. #D2B799)	❌	Returns a specific hex color code representing the detected skin shade, useful for precise shade matching.
Skin Age	skin_age	Classification	Integer (18 – 60)	❌	Perceived biological age of the skin based on its condition. Range: 18 to 60.
T-Zone	t_zone	Zone Classification	Oily / Dry / Normal / Combination	✅	Independent skin type classification for the T-Zone (forehead, nose, chin) with annotated image. Available via API.
U-Zone	u_zone	Zone Classification	Oily / Dry / Normal / Combination	✅	Independent skin type classification for the U-Zone (cheeks, jawline) with annotated image. Available via API.
Acne	acne	Key Condition	Integer (0 – 100)	✅	Detects whiteheads and inflamed pimples. Returns annotated image highlighting affected areas.
Wrinkles	wrinkles	Key Condition	Integer (0 – 100)	✅	Analyzes fine lines and deep wrinkles on the forehead, eye area, and folds (nasolabial, marionette lines).
Pores	pores	Key Condition	Integer (0 – 100)	✅	Measures pore visibility and density across the forehead, cheeks, and nose.
Eye Bags	eye_bags	Eye Area	Integer (0 – 100)	✅	Measures lower eyelid puffiness and topography changes in the under-eye area.
Dark Circles	dark_circles	Eye Area	Integer (0 – 100)	✅	Detects blue (vascular) or pigmented (brown) darkening around the eyes.
Post Acne Scars	post_acne_scars	Specific Issue	Integer (0 – 100)	✅	Evaluates visibility and depth of post-acne scar tissue on the face.
Whiteheads	whiteheads	Specific Issue	Integer (0 – 100)	✅	Detects density of closed comedones (whiteheads) across the face.
Pigmentation	pigmentation	Specific Issue	Integer (0 – 100)	✅	Analyzes melanin distribution and focal pigmentation patches on the forehead, cheeks, nose, and chin.
Hydration	hydration	Specific Issue	Integer (0 – 100)	✅	Evaluates visual signs of skin moisture levels, detecting dryness or dehydration.
Redness	redness	Specific Issue	Integer (0 – 100)	✅	Identifies overall or localized reddish spots caused by irritation, inflammation, or flushing.
Projected Skin (1 mo / 3 mo)	—	Projection / Forecast	N/A	✅	AI-based projection of how the user's skin may change over 1 and 3 months under current trends.

Score Severity Guide

All scored concerns use a standardized severity scale from 0 to 100:

Score Range	Severity	Meaning
0 – 79	Needs Attention	The concern is prominent and may require targeted skincare
80 – 95	Average	Moderate condition with room for improvement
96 – 100	Good	Healthy range with minimal or no concern detected

note

Note: This scoring applies to all scored concerns (Acne, Wrinkles, Pores, Eye Bags, Dark Circles, Post Acne Scars, Whiteheads, Pigmentation, Hydration, Redness) and the overall Skin Score. Classification metrics (Skin Type, Skin Tone, Skin Shade, Skin Age) use categorical or numeric values instead.

How Does It Work?

GlamAR’s AI Facial Skin Analysis follows a streamlined process designed for speed, accuracy, and easy integration.

1. Image Capture: The system accepts input from a live camera feed or an uploaded image.
2. ML Inference: The captured face is analyzed using GlamAR’s trained Convolutional Neural Network (CNN) models.
3. Result Generation: The model detects and scores 14+ skin metrics, generating both structured data and an annotated image output.
4. Visual Feedback: The results are returned to the client as a JSON response, including all detected metrics and the processed image.

All models are optimized for real-time performance, typically completing analysis in under 3 seconds on-device or 0.5 seconds via cloud inference.

Integration Options

Choose an integration method based on your workflow and environment:

• SDKs for real-time camera capture and instant on-device analysis. Available for Web, Android, and iOS.
• APIs for backend or batch processing. Send image inputs and receive JSON results with detected metrics and annotated visuals.
• Plugins for quick, low-code setup on Shopify, Webflow, or Mirror UI modules. Ideal for non-technical teams.
• Console manages datasets, test reports, view logs, and monitor model performance.

Note:

• Use SDKs for real-time camera mode.
• Use APIs for batch or backend-triggered scans.

Setup Workflow

A typical Skin Analysis setup follows this flow:

1. In the GlamAR Console, create a new Skin Analysis application. Each app generates a unique Application ID for integration and analytics tracking.
2. Set up your environment (development or production), generate API keys or tokens, and configure domain whitelisting.
3. Use the SDK for real-time camera capture and instant results, or the API for backend or batch image analysis.
4. Run sample scans to verify detection accuracy and JSON response structure, including annotated image results.
5. Integrate the workflow into your live app, kiosk, or platform. Track scan volume, performance, and diagnostic trends through the Analytics dashboard.