Applying AI to create facial recognition software
Computer Coding facial recognition is similar to the steps our brains follow to process and recognize the many faces we see each day. This involves both:
- Face detection – identifying the pixels which represent the face in a given image, also referred to as the pre-processing phase
- Face recognition – associating the detected face to a reference from the database, or identifying a face match
A computer program that tests images based upon features is a classifier. Classifiers are trained on thousands of positive (face region) images or negative (non-face background) images to learn how to classify a new image correctly. Using a Python script with a ‘detect’ function, the script opens the video stream and runs in an infinite loop, identifying each beginning and end of frame. Then, the frame is converted to gray to serve as input to the detect function. Finally, if a face is identified within the frame, the script saves a JPEG file – either as the whole frame or only the detected faces.
Impact Of Discovery
Airports, trains and bus stations are already deploying AI to identify potential security threats, creating intellectual systems that can function as an intuitive ‘robotic’ eye for real-time detection of unattended baggage . Additional AI applications that use computer vision include:
- Advanced driver assistance systems (ADAS) and autonomous cars
- Image recognition, object detection and tracking, and automatic document analysis
- Face detection and recognition, normally used for security issues
- Medical image processing
- Internet of Things (IoT) applications
Facial recognition systems are also becoming popular in commercial applications, such as payment authentication and the to prevent illegal fishing. monitoring of commercial fishing vessels
Expected Time On Market
Its currently on the market. Airports, train stations, bus stations and commercial applications for example are using it already!