AI-Based Virtual Try-On System with Automatic Cloth Extraction and Real-Time Body Tracking
Budget: ₹12,500 – ₹37,500 INR
We are looking to develop an advanced Virtual Try-On system to be integrated into our existing Web application. The system should allow users to try clothes (listed in our app) in real-time using live camera video.
The system must support:
Automatic cloth extraction from product images (2D or 3D)
Real-time body tracking using camera
Cloth overlay aligned to body pivots (shoulder, waist, etc.)
Dynamic movement of clothes according to user’s body motion
Scalability to support multiple products in the catalog
Scope of Work
1. Automatic Cloth Cropping (AI Segmentation)
From product images (model images or flat-lay images), the system should:
Automatically detect and extract only the garment
Remove background and human model if present
Output should be a clean transparent PNG or structured 3D mesh
The system must work for multiple clothing categories (shirts, t-shirts, dresses, etc.)
Possible technologies:
AI segmentation models
Computer vision-based object detection
2. 2D to 3D Conversion (If Required)
If product images are 2D:
Convert garment into 3D mesh suitable for try-on
Define garment pivots (shoulder, neck, waist alignment points)
Maintain realistic fabric alignment
If products are already in 3D:
Optimize meshes for real-time rendering
3. Real-Time Body Tracking
Using live camera feed:
Detect human body landmarks
Track shoulder, waist, chest, hip, arm positions
Maintain stable tracking during movement
Possible reference technologies:
Pose estimation models
Depth-based body tracking
4. Cloth-to-Body Pivot Mapping
Match garment pivot points with body landmarks
Maintain proper scaling based on user body size
Cloth must move dynamically with:
Arm lifting
Body rotation
Leaning
Walking
5. Live Try-On Rendering
Real-time overlay of garment on live video
Maintain frame rate performance (minimum 20–30 FPS)
Support Android and iOS devices
Optimize for mobile performance
6. Multi-Product Scalability
The try-on system should work for all products listed in the app
No manual pivot creation per product (preferred)
If manual mapping is required, provide scalable backend tool to manage it
Deliverables
AI cloth extraction module
Real-time body tracking module
Cloth-to-body alignment engine
Mobile SDK / API for app integration
Admin panel (if required) for product upload & pivot adjustment
Documentation & deployment support
Preferred Technical Stack
(Open to suggestions, but experience in the following is preferred:)
AR frameworks
3D engines (Unity / Unreal)
Computer Vision & AI models
Web integration
Real-time rendering optimization
The system must support:
Automatic cloth extraction from product images (2D or 3D)
Real-time body tracking using camera
Cloth overlay aligned to body pivots (shoulder, waist, etc.)
Dynamic movement of clothes according to user’s body motion
Scalability to support multiple products in the catalog
Scope of Work
1. Automatic Cloth Cropping (AI Segmentation)
From product images (model images or flat-lay images), the system should:
Automatically detect and extract only the garment
Remove background and human model if present
Output should be a clean transparent PNG or structured 3D mesh
The system must work for multiple clothing categories (shirts, t-shirts, dresses, etc.)
Possible technologies:
AI segmentation models
Computer vision-based object detection
2. 2D to 3D Conversion (If Required)
If product images are 2D:
Convert garment into 3D mesh suitable for try-on
Define garment pivots (shoulder, neck, waist alignment points)
Maintain realistic fabric alignment
If products are already in 3D:
Optimize meshes for real-time rendering
3. Real-Time Body Tracking
Using live camera feed:
Detect human body landmarks
Track shoulder, waist, chest, hip, arm positions
Maintain stable tracking during movement
Possible reference technologies:
Pose estimation models
Depth-based body tracking
4. Cloth-to-Body Pivot Mapping
Match garment pivot points with body landmarks
Maintain proper scaling based on user body size
Cloth must move dynamically with:
Arm lifting
Body rotation
Leaning
Walking
5. Live Try-On Rendering
Real-time overlay of garment on live video
Maintain frame rate performance (minimum 20–30 FPS)
Support Android and iOS devices
Optimize for mobile performance
6. Multi-Product Scalability
The try-on system should work for all products listed in the app
No manual pivot creation per product (preferred)
If manual mapping is required, provide scalable backend tool to manage it
Deliverables
AI cloth extraction module
Real-time body tracking module
Cloth-to-body alignment engine
Mobile SDK / API for app integration
Admin panel (if required) for product upload & pivot adjustment
Documentation & deployment support
Preferred Technical Stack
(Open to suggestions, but experience in the following is preferred:)
AR frameworks
3D engines (Unity / Unreal)
Computer Vision & AI models
Web integration
Real-time rendering optimization