Face Deduplication Collection

TELUS is seeking participants to collect a large and diverse dataset of facial images to support machine-learning research and facial recognition model training. The focus is on capturing real-world variations in lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. Participants will be responsible for capturing three types of images: current neutral selfies, current head-pose captures, and historical facial images. Current neutral selfies should be clean frontal selfies with natural variation in appearance and surroundings. Current head-pose captures involve selfies taken in assigned head directions to introduce pose variation. Historical images are older photos from participants' galleries to capture natural aging and long-term appearance changes. No specific education is required to participate in this project. Participants must submit a minimum of 20 valid images to qualify for payment, with a maximum payout based on 24 accepted images. Due to the strict automated and manual Quality Control (QC) process, submitting 30 images is recommended to ensure enough images remain valid after review. What the role asks for: - 20 valid images submitted - 30 images recommended for submission - No specific education required