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Face Tracking

Everything about Face Tracking


What is Face Tracking Technology?

Face Tracking is the means of identifying or verifying a human face from a digital image or video frame. It initially started as a computer application, but more recently, Face Tracking has been applied to mobile platforms and even robotics.

Face Tracking Technology can be used online or offline. When used in online mode, a face is tracked during a live feed, while the video is being captured. Therefore, only current and previous frames can be used to extract and exploit information for tracking and the efficiency requirements for doing so are quite strict. In offline mode, the information of any frame can be used to guide tracking since the whole video file is generated ahead of time.

Why is Face Tracking important?

Face Tracking can give greater accuracy than previous recognition methods like iris and fingerprint recognition. It has also proven to be more secure, and so harder to hack, making it increasingly important for use in security systems. This has given it a powerful role in security, business, and in gaming.

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What are the uses of Face Tracking?

The adoption of facial recognition systems has allowed social media platforms to increase their functionality and this has lead to a wider usage. An example of this are sites that use apps where users can change their appearances using a selection of filters. The gaming world also uses facial recognition, allowing players to become avatars, making them “realistically” enter a game and play as themselves.

Face ID has also been pioneered as a successor to Touch ID. This gives greater mobile device security and provides a system that can even function in the dark.

Border forces and immigration services around the world are increasingly using automated facial recognition systems to compare the faces of travelers with the data imbedded in their passport microchip. Also, Police forces are now using face recognition systems to observe large events, assist in investigations, and make positive IDs of suspects.

Face Tracking software can be used by businesses and organizations as a means of automating staff tracking systems while among other commercial uses are customer profiling, virtual glasses for opticians and virtual makeup for theatre or beautician work.

How does Face Tracking work?

Face Tracking generally works by comparing selected facial features from an image with faces stored in a database. This can be done using two methods:

The geometric method:
The geometric method uses algorithms set to identify the size, shape, and relative position of the eyes, nose, cheekbones, and jaw.

Photometric method:
Photometric facial tracking is where each image has a value dependent on its features. This value allows images to be compared with stored templates.

Great advances are being made in 3D Facial Recognition where several tracking cameras work together to capture the shape of a face and highlight details such as the nose, chin, and eye sockets. The major advantage is that changes in ambient light or the viewing angle do not affect 3D images.

A more recent advance is Skin Texture Analysis where algorithms turn the unique markings on a person’s skin into a skin print. It is so accurate, it can even tell the difference between identical twins, something existing systems are unable to do.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.