The goal of this project is to collect a large and varied dataset of current neutral selfies, head-pose captures, and historical facial images to aid machine learning research and improve facial recognition models at TELUS. The emphasis is on capturing real-world variations in lighting, poses, expressions, accessories, environments, and aging to enhance model accuracy and robustness. The collection includes:

Responsibilities:

• Current Neutral Selfies – clean frontal selfies that serve as high-quality identity references, showcasing natural variation in appearance and surroundings. • Current Head-Pose Captures – selfies taken in designated head directions to introduce pose variation. • Historical Images – older photos from participants’ galleries to reflect natural aging and long-term appearance changes.

To qualify for payment, you must submit at least 20 valid images. The maximum payout is based on 24 accepted images. Given the strict automated and manual Quality Control (QC) process, we highly recommend submitting 30 images to ensure that enough remain valid after review.

The project compensation rate is $0.55 USD per accepted image.

Note: Please use a Gmail address as your primary account when applying for this project.

Requirements:

No specific education is required to participate in this project.