Visual Search Makes Imagery Shoppable

Visual search uses image recognition technology that leverages sophisticated algorithms to allow anyone with a smartphone to identify products found online or in the physical world—all with the

aim of shortening the purchasing path from inspiration to transaction. 

A range of start-ups, including ASAP54, Snap Fashion, Slyce and Style-Eyes, have tapped the promise of visual search to launch “Shazam for fashion” apps. Each uses a slightly different approach to identify products — ASAP54, for example, augments its service with human experts and crowdsourced results — though they all share a core technology platform built upon artificial intelligence systems that mimic the way humans recognise objects.

A new player in the fashion image recognition game is London based Cortexica, which is approaching the business of visual search for fashion retail a little differently. Instead of building its own consumer-facing app, it has set out to deliver visual search as a service.

The details of how visual search works are complex but the potential benefits for shoppers are clear. A demo reveals how you can snap an image of a jacket on a mobile phone and the software can isolate the pattern on that jacket and then search for other kinds of garments with an exact or similar pattern. It’s an intuitive enhancement of an already existing shopping behaviour (product search). Instead of hunting out your dream item, the most suitable products can find you – based on a single image. The technology, funded by Imperial College London, uses software developed during a seven-year-long research project by bioengineers exploring how the human brain processes images. It is set to debut this summer in partnership with a large US retailer.

For an interview with Cortexica’s Chief Executive Ian McReady visit the Business of Fashion.

Sources and further reading: FT.com, Business of Fashion, Crunch Base