Ofwat’s ‘DPC by Default’ for PR24: How water…
Detect and recognize faces from reference images
This effective AI-powered tool compares the data saved on its database with the analyzed face to determine who it is. In addition to AI, facial recognition technology combines 3D mapping, biometric techniques, and deep learning. Combining these four technologies is necessary to analyze and compare a person's face to identify it. The boom in GPUs (Graphical Processing Units), Big Data, and neural networks enormously boost the developments in authentication systems.
Today the visual recognition algorithm is considered one of the most effective and efficient for identifying individuals. This market has experienced substantial growth in recent years. She most certainly retains in 2022.
The first step is to locate an individual's face in a photo or video to convert its different information and characteristics into data. The second phase compares the data with the faces exposed in a database.
The facial recognition device works like this:
Facial recognition software analyzes about 80 facial features, known in jargon as nodal points. It can be the length or thickness of the nose, the distance between the eyes, the shape of the cheeks, the width of the jaw, etc.
These elements, which are very different depending on the person, make facial recognition more precise. They are measured to create a digital code called “faceprint,” which allows listing the face in the database).
Today, these applications are crucial in areas such as security and surveillance (in airports, in the streets of certain cities, inside banks, etc.) and tourism and, more generally, marketing. Another example of the use of facial recognition is smartphones. To unlock the keypads, users present their faces to the front camera. Social networks, Instagram, Snapchat, Twitter, or Facebook
To learn more about Heka and its ecosystem