VISION IN RETAIL
bestowed by the Embedded Vision Alliance – also has plans to open a very large demo store in the San Francisco Bay Area later this year. AiFi’s cashier-less technology solution combines a network of sensors and ‘sophisticated camera technology’, which it claims can adapt to any size of store and track hundreds, or even thousands, of shoppers and products using low-power mobile devices and edge-based processing. Additionally, a fourth startup, Aipoly – also
based in San Francisco – is, like Standard Cognition, developing a camera-only cashier-less store concept. Te firm trains its system by using a simulated environment to generate data of a store and its products. ‘All we have to do is place each product inside a machine for five minutes, and voilà, the AI will learn to identify it in all plausible situations,’ the firm explained. Lastly, a fiſth startup in the San Francisco Bay
Area, Inokyo, has also opened a prototype store to demonstrate its solution and gather data in order to train its AI technology. For this concept, however, rather than using weight sensors on the shelves – as Amazon Go does – to confirm whether a product has been taken, Inokyo instead equips its shelves with another set of cameras, adding them to those already on the walls of its shop. Cashier-less technology has not only caught
the attention of startups in Silicon Valley, however. Earlier this year in Israel, startup Trigo Vision announced its successful $7 million seed funding round and the development of a
camera-only cashier-less solution that requires a significantly lower number of cameras compared to the other solutions currently being developed. Speaking to Imaging and Machine Vision Europe, Jenya Beilin, COO of Trigo Vision, explained that the firm is able to achieve this thanks to the unique and proprietary algorithm that it uses to process the images from its camera network. ‘Other systems invest in advanced hardware to
Budding startups are
racing to develop their own take on cashier-less technology in pursuit of a bigger prize
overcome the challenges of computer vision,’ he said. ‘Yet we are able to reduce the number of cameras used by enhancing our soſtware.’ Trigo Vision is also targeting a scalable
cashier-less solution that can be implemented in retail outlets, ranging from small convenience stores to large supermarkets. To do this it is using cameras that are both basic and affordable, in order to minimise cost and enable a swiſt and simple deployment. ‘We are using basic IP cameras without any sophisticated technology, primarily for scalability and cost-effectiveness,’ Beilin confirmed. IP (internet protocol) cameras are commonly
employed for security and surveillance, and can send and receive data via computer networks and the internet. Such devices are commonly available for under €50. While these systems are indeed very affordable and thus suit the price-critical characteristic of the retail sector; according to Beilin, issues caused by factors such as changes in lighting, fast-moving people, occlusions in a busy shop, and other vision- based challenges – which have already proven to be a challenge for computer vision and AI systems – are even more evident when using basic cameras. ‘However, with Trigo Vision, we have managed to overcome this by developing highly sophisticated algorithms, rather than leveraging advanced expensive hardware,’ he said. ‘We believe this is what makes our system unique and where our competitive advantage lies.’
Penetrating the market In order for the cameras of the machine vision industry to penetrate the cost-sensitive retail market, the cost of the technology has to first come down, according to Fischer at Basler. ‘Typical manufacturers of machine vision
cameras hardly meet the expected price point [for retail], as the technical requirements [of machine vision] do not fit with the ones from the retail market,’ he confirmed. ‘Tey need a frugal design and a product concept for a dedicated market approach. Cost to design and price/performance need to be optimised, ideally through a disruptive innovation.’ According to Mark Williamson, managing
director of corporate market development at Stemmer Imaging, for 3D imaging cameras such decreases in cost are already underway, thanks to a recent increase in the use of 3D imaging in mobile phones that has resulted in the mass production of powerful image processing chips. ‘Intel have developed an ASIC that can
perform image processing that they are producing in high volumes and selling to mobile phone companies for applications like facial recognition, such as the functionality in the new iPhone X,’ Williamson explained. Tis mass-production allows the price of the ASIC to be brought down, which in turn brings down the price of the cameras using it. Stemmer Imaging was recently appointed
Trigo Vision’s highly sophisticated algorithms enable it to offer a cashier-less shopping experience using simple IP cameras 56 Imaging and Machine Vision Europe • October/November 2018
as a supplier for Intel’s Realsense technology product line, a range of vision processors, depth cameras, and depth modules that together offer a combination of depth sensing and full colour HD images via Intel’s high-performance, mass-produced ASIC chips. One particular Realsense system that Williamson believes has
@imveurope
www.imveurope.com
Trigo
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72
