2022–2023
Face mask detection
Real-time COVID-19 mask compliance from live video, plus one-shot face verification from a single reference photo.
The problem
Vision problems in the wild are never clean. A CCTV frame in a crowded corridor has to answer 'is this person masked?' in real time, at a glance, under bad lighting. A face-recognition gate has to tell two strangers apart from a single reference photo.
The approach
- 01
Real-time mask detection with YOLO + CNN
During COVID-19 I built a mask-compliance detector: YOLO locates every face in the frame and a CNN classifier calls masked vs. unmasked, fast enough to run live on a video feed rather than batch-processing stills.
- 02
One-shot face recognition with Siamese networks
Instead of training a classifier per person, a Siamese network learns a similarity metric, so a single enrolment photo is enough to verify identity at the gate, and adding a new person needs no retraining.
The result
- Real-time live mask-compliance detection on video, not batch
- ~95% conf. mask-detection confidence (illustrative)
- One-shot face verification from a single reference photo
This is where the thread of my work starts: everything from clean pixels to a usable decision. The same instinct later drove the peer-reviewed LCBVAE research on dotted Arabic dates, decode a clean signal out of noise, whether the output is a mask alert, an identity, or a parsed ID.
Built with
- YOLO
- CNN
- Siamese networks
- FaceVGG
- OpenCV