Facial Recognition Solution for New Age

VIVOTEK, the leading global IP surveillance provider, strives to provide comprehensive security solutions and launches the first-ever facial recognition camera that integrates edge computing to help enterprises quickly identify the gender and age of people in the video on edge, as well as those who are wearing masks. The camera has a built-in memory card with facial data storage of up to 10,000 profiles and achieves a 99% accuracy rate of detection. The camera can also target specific person/face for real-time alarm and its software and hardware meet the standards of the U.S. National Defense Authorization Act, building an environment people can live in with peace of mind.

By: Djordje Bacic, VIVOTEK; E-mail: djordje.bacic@vivotek.com

VIVOTEK builds into the software of FD9387-FR-v2 Facial Recognition Camera the SAFR Inside AI facial recognition platform developed by SAFR from RealNetworks, LLC., which is combined with the camera’s powerful edge-computing capability to significantly enhance the efficiency of analysis. The camera’s functions include real-time facial detection and tracking; early warning of strange faces; and image privacy mode for sensitive areas, avoiding sharing of the video with a third party. Moreover, the camera is equipped with strong cybersecurity protection capability with fully encrypted data storage and transmission, safeguarding user privacy.

VIVOTEK FD9387-FR-v2 Facial Recognition Camera is suitable for building automation/ access control systems of banks, retailers, and buildings; among which, the build-in system is open to integration with business intelligence (BI) services, especially customer service of luxury retail, which sends a real-time notification when VIP customers walk into the store, enhancing service quality and standards; effectively tracks and detects person of interest (POI), making it a crucial aspect of a smart building—through list management, unauthorized visitors will be reported and recorded in case of future investigations.

What is Facial Recognition?

Facial recognition biometrically identifies facial vectors and features, matching them with pre-enrolled individuals. Recent advancements in AI technologies, based on deep neural networks (DNNs), have dramatically improved precision, unlocking a wealth of new use cases.

The technology leverages proprietary AI algorithms and mathematical equations to create an individual’s template by measuring facial variables – nose depth and width, forehead length, and eye shape. Facial recognition then compares the generated template with existing templates in a database. If there is a match, it can confirm an individual’s identity.

How Does Facial Recognition Work?

Facial recognition is by far the most powerful and relevant AI biometric technology. It has vast abilities and can carry out several tasks beyond face detection and recognition. The key features of a facial recognition engine are:

Face detection

Face detection is the first step the engine takes to confirm the presence of faces as they appear on a live camera feed, a video recording, or as it scans still image captures. The whole field of view is scanned for any area containing full or even partial human faces. Fast and precise face detection is a critical first step to ensure the performance of the entire facial recognition process.

Face feature extraction

After face detection, feature extraction is the next step. The engine first extracts an n-dimensional vector set (a template) from the facial image. Achieving very high precision requires a high “n” value. To fully ensure privacy, no actual images of faces are stored on our camera. Next, the template extracted from an individual’s face is used for matching or searching.

Face match

If the goal is to verify a person’s identity, in other words, to answer the question, “Is this person whom they say they are?” then the facial recognition engine performs a 1:1 face match. If they are already enrolled, the engine extracts a facial template from the camera feed’s live view and checks if it matches the template on file for this person.

Face search

If the goal is to answer the question, “Who is this person?” the engine completes a face search. It compares the individual’s facial template to the pre-enrolled faces in the database and confirms the person’s identity if it finds a match. The most common use of face search is a security and surveillance system using a camera to verify that a person belongs to a particular company – if their face was pre-enrolled in the company’s facial database, face search will confirm it is them and grant them access.

How Facial Recognition Will Transform Biometrics

Facial recognition technology is poised to make our world a better place. But, to do so, individuals need broader levels of education on ethical implementation to feel more comfortable with, and accepting of, businesses that have openly adopted AI biometric technology as a new, safe standard.

Facial recognition, and the potential it holds, is a more positive advancement than detractors would like to admit. It is businesses keeping their employees safe by automating secure access control in the office. It is retailers enhancing customer experiences in their stores. It is manufacturers simplifying access to their tiers of restricted areas. It is banks and fintech companies introducing much stronger authentication and cutting-edge security controls. And that’s just the tip of the iceberg.

Facial recognition is the future of AI biometric technology. The industry needs to better educate consumers and debunk the many falsehoods circulating about this technology while explaining its positive value and potential for good. Facial recognition also needs to be appropriately regulated to not hinder innovation but bring forth its many benefits.