A beginner’s guide to face detection technology
Face detection in visual data is now possible because of developments in artificial intelligence and computer vision. The use of this varies greatly, ranging from facial recognition, biometric authentication and video redaction for data privacy compliance.
What is face detection?
Face detection, also known as facial detection, is a computerised technology that uses AI to locate and recognise the faces of people in images and videos. Although this type of technology is used for identifying faces (i.e. facial recognition), this technology can be useful for other biometric solutions that do not mean identification - such as video redaction. It is widely used in different industries from biometrics to law enforcement, and private security to entertainment.
A huge dataset of photos with annotated faces is utilised to train a machine learning model for face detection. The model picks up on patterns in the photos and develops the ability to distinguish between what is a face and what is not a face.
The quality of the input image, lighting situations, the size and positioning of the face, and the presence of occlusions like glasses, masks and facial hair all have an impact on face detection technology. Additionally, elements like the training dataset, the algorithms utilised and the processing power available may have an effect on how well the face identification system performs.
Why is face detection a useful technology today?
Face detection technology is used across all sectors, and not only for the purpose of identification.
Across Retail and Security, automated face detection programmes help gather accurate data, analyse surveillance and eliminate human survey errors. This boosts efficiency as commercial businesses discover how customers react to certain triggers.
In day-to-day life, face detection is used across most smartphones as a way to unlock devices, via ocular mapping and recognition.
Face detection can also be successfully used for face redaction in video. Think of it as the reverse engineering of detection algorithms to safeguard an individual’s data privacy. Face detection points out an identifiable face in digital footage, and then blurs that face to protect people’s privacy.
This is how our product, Secure Redact, works. We use face and number plate detection technology for the sole purpose of blurring personal data to protect individual privacy and comply with data legislation.