Face recognition is a method of identifying a person or an object through photographs, videos, or in realtime. It is a biometric identification that uses various features and patterns of face to recognize people and objects. Face recognition with artificial intelligence and machine learning capabilities allow the software to map and distinguish facial features. After mapping the face, it compares the features with data stored in the database.
In the recognition process, AI plays an important role. In artificial intelligence, we have computer vision works through measuring nodal points on a face to make a face-print. This faceprint is a unique code that is applicable only to a particular person and this enables identification.
In this blogpost, we at Oodles, as a computer vision development company, share the nuts and bolts of face recognition and its business use cases.
Deep learning is a subset of machine learning which uses Machine Learning algorithms and a huge amount of data to train a neural network for enhancing accuracy. It learns through an Artificial Neural Network which is considered as more human-like.
It is also known as Biometric Artificial Intelligence.face recognition detects and verifies an individual digitally within a data through Deep learning becomes accurate and stores the data in the database. It works like a human brain.
Deep learning algorithms enhance its experience using old and new data, through this it can make a reliable prediction and also present better results.
Face detection differs from face recognition it involves the detection of a face within a digital image or video. It can only identify the person is present or not but it cannot identify that person. Face detection is a subset of face recognition whereas face detection is also used in a camera to auto-focus on the face or objects.
1. Unlocking Phones
2. Security cams.
3. Diagnose diseases.
4. Law enforcement.
Face recognition is an upcoming technology that can provide many benefits. AI’s underlying machine learning development and deep learning techniques are beginning to save huge time and cost for surveillance businesses. This can replace IDs with facial recognition in passports, credit card pins but as it is very costly to use and implement it'll be a challenge to implement these things on a large scale.