VISION IN RETAIL


using hundreds of overhead cameras – which initial patent filings suggested could include depth sensing cameras, RGB cameras, and infrared sensors – in combination with weight sensors, computer vision and deep learning algorithms. Together, the systems are able to identify exactly when and what items are picked up or placed back on shelves by individual customers, enabling their Amazon accounts to be billed accurately as they leave. Amazon is considering a plan to open up to 3,000 of these stores across the US by 2021, according to media outlet Bloomberg, which would make it one of the largest retail chains in America.


Tracking customers Meanwhile, however, in San Francisco, California, a number of budding startups are racing to develop their own take on cashier-less technology in pursuit of a bigger prize. Rather than looking to compete with the 155,000 convenience stores in the US by introducing their own chain of automated stores, the firms are looking to augment the existing stores with their own suite of computer vision technology. Standard Cognition, for example, hopes


sensors, computer vision and deep learning algorithms to automate the way customers pay for products. In these stores, customers no longer have to queue up and pay for their items using a standard checkout system; instead they are simply billed automatically as they exit the premises, according to whichever items they have picked up and kept during their trip. Tis extraordinary development has been


made possible due to the combination of vision, sensor and deep learning technology being able to keep track of individual customers and detect exactly what items they pick up aſter they enter and move throughout the store. A personal online shopping cart is created and continuously updated for each customer as they accumulate items during their visit, which is then automatically purchased and charged to a pre-existing online account as they leave. Te first of such stores to open in the US was


Amazon’s first ‘Go’ store in Seattle, Washington, at the start of the year, which has since been followed by two further stores in Seattle and another in Chicago, Illinois. Te shops operate


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to equip convenience stores with its solution that, unlike Amazon’s, relies solely on camera technology – without needing additional sensors – to track individual customers and items around the premises. According to the firm, this makes the technology scalable, reduces its operational complexity and the amount of required maintenance, and enables a lightweight installation process that causes minimal disruption to the store – it can be done overnight and without having to rearrange any shelves or products. Te firm raised a total of $10.6 million across three separate funding rounds between August 2017 and July 2018, and is now demonstrating its solution at a prototype store open to the public in San Francisco. Not only is Standard Cognition’s camera


network capable of tracking multiple customers each picking up individual items, but the solution can also identify when multiple items have been picked up simultaneously by individual customers; detect when items have been put down by customers around the store (and remove these items from their online shopping cart); and identify when items have been passed or even thrown between customers. In doing this, the solution also produces a wealth of data on customers’ shopping preferences and behaviour for the retailer to examine. Standard Cognition assures that this data is captured anonymously and without collecting any biometric information – such as


facial recognition data – from customers. Each year US retailers experience $130 billion


loss in profit due to cashier-related overheads and shrinkage such as shopliſting, administrative errors and damaged goods. In addition to rising minimum wages and rent, on top of already thin profit margins, many retailers are struggling to compete with larger chains and online options such as Amazon, and could eventually go out of business. ‘We want to help retailers, both small and


large, thrive and eliminate the cumbersome, expensive checkout experience as it exists today,’ commented Michael Suswal, co-founder and chief operating officer of Standard Cognition. ‘We saw the need in the market for a better commerce solution for brick-and-mortar retailers that would leverage the latest AI technology to help them dramatically cut costs, get better analytics, get insight into inventory and shrinkage, and improve the checkout experience for their customers.’ Te firm announced in July that it is installing


systems for multiple retailers around the world, with the first revealed as Paltac – the largest


A number of new,


futuristic stores have been established across the US


Japanese wholesaler of fast-moving consumer goods and over-the-counter drugs, which has over $8.6 billion in annual revenues, and services thousands of retail stores across the country. ‘In Japan, retailers considering autonomous


checkout have [so far] really only had RFID or scan-and-go type options,’ said Yohei Nishiyama, general manager of Standard Cognition’s recently established Japanese office. ‘Both are rather old fashioned. Standard’s approach is very different – it has a much lighter footprint, it’s easier for shoppers, and it provides a lot of data to retailers without compromising shoppers’ privacy. Standard’s solution has been very well received by Japanese retailers.’ ‘When we show them what Standard can do


with very little hardware and no scanning at all, they are generally blown away,’ Suswal added. Also in San Francisco, another startup, Zippin,


which as of August had secured $3 million in seed investment, has opened a prototype store to demonstrate its cashier-less concept, which like Amazon’s uses shelf-based sensors, in addition to cameras, to confirm purchases. Meanwhile, AiFi, another startup and a finalist at this year’s Vision Tank Award –


October/November 2018 • Imaging and Machine Vision Europe 55


Trigo


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