If you want to buy a table just like the one you saw at a friend’s place or in a restaurant or wish to choose furnishings the way professionals do, a new app developed by Cornell University researchers, including one of India-origin, can help.
All you have to do is click a picture of the item and submit it. Given a photo of a chair, lamp or some other item, the new service can tell you who makes it and where to buy it from, and show you pictures of how it might look in various rooms.
In the future, the researchers said, similar systems might be developed for other kinds of products, such as clothing and fashion.
Professor of Computer Science Kavita Bala and doctoral candidate Sean Bell described their method for “learning visual similarity for product design” in a paper published in the journal ACM Transactions on Graphics.
“It seems a lot of people want to buy things they see in someone else’s home or in a photo, but they don’t know where to look,” Bell said.
The system relies on “deep learning”, a neural network that enables a computer to match a submitted photo with a vast database of “iconic images” from manufacturers’ catalogues or specialised websites devoted to home furnishings.
A neural network is a computer programme inspired by the working of neurons in the human brain.
Rather than force the computer to go through the entire database looking for a match, the system begins by using the neural network to generate a “fingerprint” of a submitted image, based on very broad characteristics of how the pixels are arranged.
Then the computer can search just a local area of the database, analogous to searching for a phone number in just one area code.
Bala and Bell have formed a start-up company, GrokStyle, to offer the service on a subscription basis to retailers and design professionals.
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