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Search algorithm uses tag locations of online photos

Posted: 05 Dec 2013     Print Version  Bookmark and Share

Keywords:algorithm  social networks  relational social image search 

Engineers at the University of Toronto have designed a new algorithm that can change the way you find photos among the billions of snaps on social media sites such as Facebook and Flickr.

The search tool developed by Parham Aarabi, a professor at the University of Toronto, and his former student Ron Appel, uses tag locations to quantify relationships between individuals, even those not tagged in any given photo.

"Imagine you and your mother are pictured together, building a sandcastle at the beach. You're both tagged in the photo quite close together," the researchers said. "In the next photo, you and your father are eating watermelon. You're both tagged. Because of your close 'tagging' relationship with both your mother in the first picture and your father in the second, the algorithm can determine that a relationship exists between those two and quantify how strong it may be."

"In a third photo, you fly a kite with both parents, but only your mother is tagged. Given the strength of your 'tagging' relationship with your parents, when you search for photos of your father the algorithm can return the untagged photo because of the very high likelihood he's pictured."

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The algorithm, called relational social image search, achieves high reliability without using computationally intensive object- or facial-recognition software, the researchers said.

"If you want to search a trillion photos, normally that takes at least a trillion operations. It's based on the number of photos you have," said Aarabi. "Facebook has almost half a trillion photos, but a billion users—it's almost a 500 order of magnitude difference. Our algorithm is simply based on the number of tags, not on the number of photos, which makes it more efficient to search than standard approaches."

Currently the algorithm's interface is primarily for research, but Aarabi aims to see it incorporated on the back-end of large image databases or social networks.

"I envision the interface would be exactly like you use Facebook search—for users, nothing would change. They would just get better results," stated Aarabi, who has been working on this project since 2005.

Another potential use for the algorithm could be map generation – something that was discovered by while testing the algorithm. Aarabi and his team tagged a few photographs of buildings around the University of Toronto and ran them through the system with a bunch of untagged campus photos. "The result we got was of almost a pseudo-map of the campus from all these photos we had taken, which was very interesting," he said.

This month, the United States Patent and Trademark Office will issue a patent for the algorithm.





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