Facial recognition
Integrate facial recognition software with your VMS to reliably detect and identify people for security and streamlining purposes.
Streamline operations and security
Identify suspects
Streamline investigations by correlating faces with events.
Automatically grant access
Simplify access control of people with video footage.
Personalize customer service
 Improve customer engagement by analyzing behavior and demographics.
Real-time identification and authentication using faces
Facial recognition is analytics software that identifies and authenticates a specific person by their facial features from an image or video. With advanced facial recognition software, additional factors such as skin tone, color and style of clothing, vehicle type, and travel direction can also be calculated.

Facial recognition software can be paired with many other technologies, including intrusion detection, license plate recognition (LPR), GPS, access control, crowd detection and city surveillance. The technology is expanding from 2D to 3D which is of particular value in identifying criminals and terrorists, in patrolling highways and in aiding forensics.

For businesses, facial recognition software can add an extra layer of security, increase efficiency of access to restricted areas, give better customer experiences, and aid investigations after an incident has occurred.
Frequently asked questions
Commonly asked questions and answers about facial recognition.

How does facial recognition work?

Face recognition camera software programs can identify and interpret complex patterns in ways similar to the human brain. The software uses biometrics to map the geometry of the face. It notes more than sixty facial landmarks, measuring and then calculating a number to represent the combined relative distances. The result is called a “faceprint”. When comparing the image input to a database of stored mathematical models of known faces, an algorithm will determine the best match and a percentage of probability of accuracy is provided. Additional related information, like skin tone, color and style of clothing, backpack detection, vehicle type, and travel direction, are also able to be determined by advanced programs.

How accurate is facial recognition?

In optimal conditions, facial recognition software can reach accuracy rates of over 99%. Accuracy can, however, deteriorate because of poor lighting, diverse faces, background noise and other factors. The software can also struggle with things like glasses, hats and hooded sweatshirts.

Where is facial recognition used?

For years, face recognition has enabled the capture of wanted criminals. Face analysis is also a crucial support for theft prevention and safety in transportation and in retail. As facial recognition increases in efficacy, so does its number of commercial applications. There is particular growth in healthcare, IT, banking and marketing. Face scanners are increasingly used to improve customer experience and increase sales, by identifying celebrities and favored customers. Thanks to deep learning-based algorithms, face analysis is able to provide identity verification with a high degree of accuracy, even outperforming human facial recognition capabilities.

What are the key features of facial recognition software?

A reliable facial recognition software needs accurate algorithms and many diverse facial features to learn from. It uses machine learning to continually improve over time and adapt to different situations. Another key feature to keep in mind is privacy and making sure that measures are available to protect this. Lastly, the software should also be easy to use to avoid human errors when using it.

What does facial recognition software look for?

Facial recognition software relies on being able to measure facial features such as the eyes, mouth and nose. When distinguishing between faces, the structure and geometry of the face is the foundation, such as the distance from forehead to chin and the distance between the eyes. Additionally, it will also look at the balance of both sides of the face, thus determining the facial symmetry. By taking all these aspects into account, the software is able to create a facial profile which will then be compared to known profiles in the database.

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