The objective of this project is to collect a large and diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training at TELUS. The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness.
The collection includes
- Current Neutral Selfies – clean frontal selfies serving as high-quality identity references, with natural variation in appearance and surroundings.
- Current Head-Pose Captures – selfies captured in assigned head directions to introduce pose variation.
- Historical Images – older photos from participants’ galleries to capture natural aging and long-term appearance changes. Qualification path No specific education is needed to perform the project task.
Compensation (optional)
Currency
USD Contact email
[email protected]
📌 Face Deduplication Collection - English (MX) (México)
🏢 Telus Digital
📍 México