LP Magazine

SEP-OCT 2018

LP magazine publishes articles for loss prevention, asset protection, and retail professionals covering shrinkage, investigations, shoplifting, internal theft, fraud, technology, best practices, and career development.

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have used facial recognition for security and/or sales and marketing. Manufacturers are certainly recognizing the potential. For example, Megvii, a Chinese startup that develops facial recognition technology, is raising $600 million in funding, most of which reportedly will be used on the company's initiative to sell more of its technology to retail stores. The need for retailers to understand customers at the individual level—not just by zip code, age, or gender—is also likely to fuel interest. A principal analyst at Forrester Research identified that goal as a top technology trend at the 2018 NRFtech conference. Lofty expectations are the result of significant technology enhancements that manufacturers have made. "A lot has happened in the last five years—and even more so in the last two or three years—especially in terms of a big leap forward in accuracy and performance," said Trepp. "We've now gotten to the level that really was sort of the promise all along, that ability to match a person who moves in front of a camera in a real-time environment." By identifying a face against those contained in a database, and doing so in real time, systems can send an immediate alert to store personnel, which allows LP to monitor or intervene with a suspicious person before a crime is committed. "That has been the big leap," said Trepp. The enhanced capability is made possible by the shift to neural networks for feature matching and a continued improvement in computing power, according to Don Knasel, CEO and founder of DeepCam, which launched Retail by DeepCam at ISC West in 2018. "All world-class facial recognition is now based on neural networks," he said. It enhances the value of systems in multiple ways, including being able to make comparisons of partial faces, when faces are captured at an angle, and has improved accuracy across demographics and despite beards, sunglasses, and hats. Also, it enhances the ability to run recognition on less expensive cameras, said Knasel, "which brings the cost of a system down by an order of magnitude." The FRT market study made note of the progress manufacturers have made, concluding that traditional technology constraints regarding camera type and lighting conditions have largely been overcome and predicting that improvements haven't yet hit a plateau. "A lot of research is being done to make the technology more efficient, and huge new players are competing in the market to develop better and more-efficient systems," according to the study. Moreover, some experts noted that since recognition is based on a fundamental human feature, rather than a type of device they interact with, FRT's life cycle could be especially long. It's still a rarity in US retail stores, but some are already having success identifying chronic returners, counterfeiters, thieves, and other persons of interest—and it's creating interest among others. "We're making scores of matches every day, and at least once a week, we get a really, really bad guy," said Trepp. Another great use, according to Andrew Chapman, senior vice president of sales at 3VR, is to identify if an individual who comes in empty-handed is shortly thereafter at the return desk carrying a package. "Some retailers use that to at least reject the return, and for that it's a great tool," he said. Better performance, lower cost, real-world uses, early adopter proof-of-concepts—it's clear why there is a buzz about facial recognition. Joel Rieger, principal consultant for Rieger Consulting, is currently helping several major retailers examine technology platforms and conduct tests. "The willingness of retail companies to engage with this type of technology is certainly on the increase," he told LPMagazine. Yet, as it looks to become another standard tool in the LP arsenal, FRT is contending with some significant historic, regulatory, strategic, and public-perception obstacles that has kept many retailers on the sideline. A Spotty History A lingering hangover of false promises may still afflict some LP leaders' attitudes toward FRT, contributing to their cautious approach to the technology. "History is against us—this idea that facial recognition technology doesn't work, it's too expensive, it doesn't work on some ethnic groups, that you're going to get false positives and a false alert two out of three times," said DeepCam's Fleischman. He sees confidence in the technology growing but acknowledges it has taken time. FaceFirst's Trepp admits that five years ago FRT systems were not delivering on their hype, including for real-time accuracy. "It put people off," he said. Joel Rieger Andrew Chapman It's still a rarity in US retail stores, but some are already having success identifying chronic returners, counterfeiters, thieves, and other persons of interest—and it's creating interest among others. 17 LP MAGAZINE | SEPTEMBER–OCTOBER 2018 AN ABOUT-FACE FOR LP?

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