{"id":337594,"date":"2017-04-05T01:05:32","date_gmt":"2017-04-04T17:05:32","guid":{"rendered":"http:\/\/techcrunch.com\/?p=1470692"},"modified":"2017-04-05T01:05:32","modified_gmt":"2017-04-04T17:05:32","slug":"grokstyle-is-putting-computer-vision-to-work-on-home-decor-with-2m-in-funding","status":"publish","type":"post","link":"https:\/\/people.utm.my\/asmawisham\/grokstyle-is-putting-computer-vision-to-work-on-home-decor-with-2m-in-funding\/","title":{"rendered":"Grokstyle is putting computer vision to work on home decor with $2M in funding"},"content":{"rendered":"

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One of the things I\u2019ve always wanted from technology is the ability to point my phone at something or take a screenshot, and have it say, here\u2019s what that thing is and here\u2019s where you can buy it. Well, my lavish consumerist dream is starting to come true, and Grokstyle<\/a> is one company working to make it so \u2014 in this case, automatically identifying furniture and home decor from just about any picture or angle.<\/p>\n

The basic idea is this: you open an app or web interface, and upload or take a picture of, say, a chair or lamp you like. Any angle, any style. The Grokstyle service immediately returns the closest matches, either including the object itself or ones very like it.<\/p>\n

That would of course be very handy for any interior decorator, but ordinary shoppers can make it work, too. See a cool lamp at Restoration Hardware but can\u2019t see yourself spending $500 on it? Maybe CB2 has something similar \u2014 Grokstyle would have hooks into individual stores\u2019 inventories so you could check that sort of thing, or sort by price range.<\/p>\n

As a business, it would offer its service as an API that retail apps or web interfaces could call. And having the deep knowledge of what different designers, rooms, and regions have put together, it could even recommend, say, an end table to go with the couch you just looked up.<\/p>\n

At heart it\u2019s all about computer vision and machine learning, of course: figuring out what the picture is of, then the contours of the piece, the dimensions, colors, and so on, and matching that info to a library of millions the company has collected.<\/p>\n

\u201cThe company started from research at Cornell,\u201d said co-founder and CEO Sean Bell. \u201cWe were focused on the question \u2018what is it?\u2019 And we developed the best tech for that problem.\u201d<\/p>\n

It isn\u2019t easy: lighting, occlusion, weird angles \u2014 not to mention the intentions of the user. Did they mean to shoot the table or the chair next to it? And is that walnut or cherry?<\/p>\n

Easy or not, they made it work, and the resulting system is so fast it almost looks fake (it isn\u2019t). Watch a prototype in action here:<\/p>\n