Is Facial recognition using AI the next big thing in Biometric ID?

Contributed by Navin Parti, Vice President, Q3 Technologies

As technology takes center stage in every job in the world “Going Digital” becomes the common refrain for enterprises, both large and small. Of the going digital areas - one of the more challenging and big potential areas is Facial recognition, using AI & Machine Learning.

With the explosion of population, enrichment of the general populace and the advancement of travel, we now have tremendous use and application of using facial data for different applications across Travel & Tourism, Retail, Healthcare, Government, and many other industries.

As a simple explanation - A face recognition system is a computer application capable of identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a face database. As devices become cheaper and requirements become important, this could extend to 3-dimesional recognition, Thermal cameras and Skin Texture analysis

By 2020, the facial recognition market will reach $6 billion worth. MasterCard has announced selfie payments – a payment method using a selfie from a smartphone to pay for a bill. Snapchat’s geo filters and special facial recognition effects are also aimed in this direction. Companies like Facebook have also been using facial recognition for quite some time now, with its tagging feature in photos. It makes recommendations on who that person is in the photo using predictive intelligence.

Let’s take a look at some further industries & areas where futuristic applications could determine the course of the industry going forward:

Government/ Identity Management

The U.S. Department of State operates one of the largest face recognition systems in the world with 117 million American adults in its database. The photos are typically drawn from driver's license photos. Though not completed, it is being put to use in certain cities to give clues as to who was in the photo.

Recently the State of Maryland in the US used face recognition to arrest unruly protesters after the death of Freddie Gray in police custody.

You can use these systems for Voter identification, census studies, healthcare interventions, BPL handouts, law and order management etc. These applications could have particular significance in populous countries like India, where while the budgets are low, we have an opportunity to leapfrog the West using the latest technology.

Retail / Emotion & Sentiment Analysis

Again facial recognition, could have tremendous positive outcomes for private enterprises. You could have a non-intervention based attendance system, retail stores could detect repeat customers and prompt salespersons to greet them by name, a retail company could analyze videos of customers as they experience marketing, products and services.

Systems now provide complete and accurate facial expression detection and frame-by-frame measurements of key emotions, as well as attention, engagement and positive or negative consumer sentiment.

These emotional recognition systems work on identifying human emotion, most typically from facial expressions. Recently, computational methodologies have been developed from multiple areas, such as signal processing, machine learning, and computer visions to detect emotions and sentiments.  Programmers often use Ekman's Facial Action Coding System as a guide.

Marketing/ Product portfolio management

Face tracking technology can also be employed for analyzing what catches the eyes of customers in the public space, in malls, showrooms etc.

We can now remotely conduct extensive market research and usability studies on how a user browses web pages, views advertisements, and reads text through the webcams of participants sitting in the comfort of their homes – further ensuring a natural environment for a widespread high-fidelity data collection.

Healthcare/ Healthcare provisioning

Easy identity management with facial recognition could facilitate easy check into hospitals, clinics and other medical facilities, in turn EMR records could be fetched in a flash, and Insurance companies could check and authorize transactions in minutes instead of hours or days.

Facial recognition could also power emotional and sentiment analysis in mental healthcare environments, as well add another piece to Telemedicine to make it a real possibility.  While telemedicine could allow doctors to remotely check patient condition, run tests, diagnose, and monitor progress – facial recognition technologies could help monitor moods & overall mental health.

In addition, face and head tracking can be utilized for physiotherapy treatment through measuring and recording of head position, gaze direction and eye closure.

Financial services/ Authentication systems

Facial recognition could ease Point of Sale payments, with no swiping of cards, and potential of reducing lines at retails counters. Mobile banking could use a high-value second factor for authentication.  Cashpoint/ATM’s could benefit from faster access and disbursement, saving monies on issue of cards, reduce lost time for consumers due to card lost/ not working etc. It could also reduce spend and inconvenience for pension and other financial disbursements that require Proof of Life for older citizens who often have to manage this with difficulty.

Challenges

A technology this promising has to have some hiccups however and this article would not be complete without talking about some of them.

Accuracy in facial recognition technology remains less than desired, though it is bound to improve significantly considering the astonishing ability of modern technology vendors to resolve problems fast. What if a malfunction occurs and it creates a problematic situation for a consumer?

A second key issue consists of privacy & consent. In today’s fast-paced digital world many consumers are concerned about the privacy aspect behind it. Consent or acquiring permission for facial recognition technology usage may be difficult to accomplish.

However, with Snapchat’s over 200 million, Facebook base exceeding 2 billion people, LinkedIn acquiring 2 new users every second with a projected goal of 3 billion (currently 467 million) where many legions of users have signed away privacy concerns, this may in fact be feasible to accomplish.

In conclusion

Many companies are hesitant towards early adoption for valid reasons - there can be ramifications due to accuracy concerns, legal/ privacy cover & other unforeseen deficiencies.

The time is ripe however for the next leap in “Going Digital” using Facial technologies. We also need to remember that we live in times where the fast adoption of technologies may make the difference between your business thriving or dying.