Face Recognition – Short Explanation

Face recognition or facial recognition uses technology to map an individual’s face visually and compares it with a database of known faces. This technology is used extensively to verify identities for personal use, but it has some privacy implications that are only now being explored.

Facial recognition technology is used around the world for a variety of different reasons. Companies like Apple, Samsung, and others have provided smartphones that use facial recognition as a means of accessing the device. Facebook and Google use facial recognition to automatically “tag” photos and create links. Law enforcement agencies use facial recognition to help find criminals. The use of facial recognition is growing daily and extends from the personal to the corporate and beyond.

Understanding Face Recognition in the Real World

Facial recognition is not overly complicated in practice. The system basically reads the geometry of a face either from a photo or a live camera feed. Measurements include the shapes of the eyes, nose, and mouth, amongst others, and also distances between different facial features.

Based on these measurements, a unique facial signature is created. This facial signature is then compared to a database of known faces. Based on the results of that comparison, appropriate decisions are made. Keep in mind; facial recognition technology is used not only for access to personal devices but also as a means of investigating crimes. As such, a “match” has very different connotations based on the motivation of the person searching.

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How Face Recognition Works in the World of AI

Face recognition has advanced dramatically over the past decade, primarily through the increasing use of big data and a type of network called a convolutional neural network (CNN). With the advent of the internet and sites like Flikr, Facebook, Instagram, and Google, the volume of images now available online is massive.

Through extensive training using these massive image libraries and CNNs, face recognition has advanced considerably in capability. Using computer algorithms, face recognition systems pick out specific details. These details, such as the shape of an eye or chin as well as the distance between features, create a facial signature or template. This template is very different from a photograph as it only includes the distinguishing features from one face to the next. By comparing the geometry, matches are made against specific criteria.

Between 2014 to 2018, face recognition systems saw a twenty-fold improvement in overall accuracy. However, this accuracy requires ideal conditions. In instances where an exact match is not available, facial recognition systems can be used to calculate a match based on the criteria set. This comparison lets the system provide several matches based on likelihood instead of a single result.

Facial and face recognition systems are here to stay. Their usefulness cannot be discounted. However, the risk of privacy needs addressing as does its use with governments that flaunt freedoms of expression.