Improving Store Security: Considering Facial Recognition Quality and Cost

Facial recognition technology could provide huge benefits when it comes to retail store security. When used properly, someone caught stealing can be stopped by the store detective or security guard who is trained in making an approach, and they advise the suspect that as a condition of not pressing charges they must enroll in the store’s LP system.

This enrollment takes the form of recording biographic and incident data as well as a facial picture. The suspect would then be advised that they are persona non grata and now prohibited from entering any other stores. With that understanding and agreement, they are free to leave without further action. By consenting to do this, the enrollee’s face is logged into the database (called a gallery), which can be shared across the entire organization . In this way if they attempt to enter another branch, that store’s FR system picks them up, and they are once again asked to leave. Additionally, by using smartphone technology, a notice can be sent to all LP associates to heighten awareness of a possible threat.

In this respect, it is a totally “opt-in” experience rather than a “capture-all” technology, which is important to remember when considering the privacy arguments circulating around the FR debate.

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Cost savings have even been quantified in terms of time. Ideally, the simple threat of immediate identification by the FR system will act as a sufficient deterrent. Approaching a suspect as they enter the store takes about three minutes. Compare this to watching a suspect go around a store and waiting for them to steal, which takes on average twenty minutes. If they are detained, that involves an average of forty-five minutes of their remaining in the store. The total time saving here per case is a minimum of one hour of a store detective or security guard’s time. It is therefore easy to make a financial case for technology making LP more cost and time efficient.

Quality, Cost, and Accuracy

Until now, one of the inhibitors to widespread adoption of FR in retail environments has been the quality of the video images. Previously, the grainy images of customers captured on predominantly analog systems have been so poor that even when LP staff were watching an event as it happened, they were hard pressed to make a positive identification. By contrast, today’s high-definition IP cameras offer crystal clear images well suited for FR. Factor in the latest software that can convert a 2D video frame into a 3D model and accurately map the contours and textures of a face, and you have a powerful surveillance system that can perform matching in the most difficult of situations.

There seems to be two separate issues at play hindering the final hurdle to wider adoption. First, although many accept that the technology is proven, it has until recently been seen as expensive to install as part of a store security system.

The second, more thorny issue—although it is had not halted the FR adoption rates—is that of privacy. The perceived expense of FR is not the matching software per se, but the installation of dedicated FR security cameras and integration with other store technology like video management systems, local area, and virtual private networks, according to Jack Ives of reconstruction technology developer CyberExtruder who, over the last 16 years, has built the software that makes robust face matching from video possible.

“System cost was a blocker. But the precipitous decline in price of high-definition cameras and the new low-cost HDCVI cameras have significantly lowered the bar and accelerated adoption,” said Ives.

“Cameras that were once costing thousands of euros can now be bought for hundreds. Labor to put the whole system together is still the larger cost, but as integrators become more accustomed to the new paradigm, that cost is falling as well. Previously a bird’s-eye view of the store entrances was the desired setup. Now, when the goal is face matching, the cameras need to be located lower in order to capture people’s features.

“One of the other early issues was that people are milling about, and the camera was only able to capture rough angles including side views, which was not conducive to matching. That is why we have developed a process of making the image a 3D model, which now provides the infinite ability to re-pose a facial picture and then carry out accurate matching.”

Access control and even replacing computer passwords with FR technology will form part of the future to reduce the chances of cyber attacks or hackers accessing personal information.

Ives said that although many companies are still using analog networks for their store security, the HDCVI camera technology produces a solution that marries a low-cost HD camera with legacy analog cabling and is FR capable.

“We have been trialing this with a couple of businesses, and the feedback is interesting because the benefit has proved greater than we all expected,” he added.

This post was excerpted from an article in LP Magazine EU that was published in 2015.

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