The Task
A client developing facial recognition and anti-spoofing technologies approached us with a clear objective: to collect a high-quality dataset for testing four types of presentation attacks — Live, Print, Crop, and Display.
Due to internal resource limitations, they needed a partner who could take over the full cycle of data collection — from sourcing participants to final validation. After reviewing several providers, the client chose Unidata for our proven track record and flexible approach.
The Solution
Preparation and Technical Briefing
We began by aligning with the client’s technical specifications and validating the workflow with a pilot phase. This ensured we were fully aligned before scaling.
Performer Recruitment and Photo Capture
Using our wide performer base, we organized the collection of five photographs per participant, each taken from specific distances and angles.
All images adhered to strict guidelines for positioning and proportions.
Spoofing Scenario Generation
To simulate various spoofing attacks, we produced supporting materials — printed versions of faces, cropped cutouts, and digital displays. These required precise execution to ensure background consistency and proportional accuracy across all samples.
Validation and Quality Assurance
Collected data underwent a two-stage validation process.
Images were reviewed for visual and technical compliance, and all inconsistencies were corrected before final submission.
The Result
- Efficient Delivery: Over 10% of the client’s total dataset was completed in just one month.
- High-Quality Data: 50 validated sets totaling 2,000 photos were delivered, covering all required attack types.
- Client Endorsement: The client praised the speed, accuracy, and process clarity, emphasizing their readiness to partner with Unidata on future projects.
