Given a photo of a chair, lamp or some other item, a new
"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," said Sean Bell, a doctoral candidate in computer science. Bell and Kavita Bala, professor of computer science, describe their method for "learning visual similarity for product design" in a paper presented at the 2015 SIGGRAPH conference and published in ACM Transactions on Graphics.
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' catalogs or specialized websites devoted to home furnishings.
A neural network is a computer program inspired by the working of neurons in the human brain. As data is passed through the network, locations in memory that are activated repeatedly are increased in value, just as a biological brain forms synapses. "Deep learning" combines several layers of neurons that represent different aspects of the data - earlier layers typically represent edges and lines, middle layers represent parts and shapes, and later layers represent entire objects and concepts.
Read more at: https://phys.org/news/2016-08-chair-app.html#jCp
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