The face mask detector we build, potentially aims at ensuring public safety. Face mask detection offers several advantages to the monitoring personnel. These include face recognition and intelligent alerts. Face mask detection at public places shall ensure public health and safety. People without a mask can be easily identified and notified to wear mask before entering places like malls or transit areas like airports, train stations, etc. Face mask detectors are useful in enterprises too. They ensure whether the workforce maintains safety standards at work.
Our face mask detection system uses AI as a tool based on deep learning algorithms. It detects face masks in public places by performing detection in real time with the help of surveillance camera network. The mask detection system detects face mask in images as well as in live video streams.
As shown in the block diagram, we get to the results o mask detection in two stages.
This is an easy method to achieve the result. The system is fed with faces, torso, hands and other parts of the body. The landmarks help the system to automatically locate the face. The system then detects the region of interest (RoI) in the faces where mask is worn. The face mask is detected in three simple steps:
The system is equipped to detect masks in images and in video streams and is capable of working with minimum computational capability while processing real time image data. It is an easy method to manage wearing of face mask in public places, specially the crowded ones.
The face mask detector can be integrated with the embedded systems and easily used at transit stations, airports, offices and other public places thus ensuring public safety.Block diagram depicting steps to build face mask detector with deep learning and computer vision algorithms is shown.