Bing is expanding its image search toolset with a new product that lets users search for specific items shown within a larger image.
They’re calling it Bing Visual Search, and it’s available now as part of the Bing’s existing image search tools. It’s pretty simple to use and pretty impressive, too.
In my first sample search, I queried Bing for landscape ideas and chose a photo that showed dozens of different plants and bushes in someone’s backyard. On the individual image screen, a small magnifying glass appeared in the upper left — clicking that launched the new visual search tool that let me pinpoint one specific plant from the dozens available. And after I did that, Bing identified my chosen plant as a snapdragon (I’m no green thumb, so can only assume that’s correct) and showed me a new set of search results just for this one plant from the original photo.
My results were a bit mixed when doing people-based searches.
For example, I searched for a photo of my favorite band, U2, but when I pinpointed a single band member, Bing Visual Search had trouble identifying matching images; it showed me photos of other singers and guitarists when I pinpointed just Bono and The Edge.
On the other hand, it correctly identified actor Ben McKenzie when I searched for him within a photo of some of the cast of the Fox TV show, “Gotham.”
Bing says its new visual search tool will work with existing internet images as well as new user-taken photos. It’s available now on Bing.com (desktop and mobile) or in the Bing mobile app. Bing is also making visual search available to developers via its image search APIs.
Some of Bing’s competitors have released or announced similar search/shop-within-an-image tools recently. Google is using product metadata to identify items seen in a photo, and also plans to launch Google Lens soon, a tool that turns smartphone cameras into a search box. Pinterest has its Shop The Look feature, which turns items inside an image into something users can buy. Even Instagram is testing a way for consumers to buy specific items seen in images.
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Author: Matt McGee
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