A new algorithm can change and simplify 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 from 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, 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, they said.
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.
"Two things are happening: we understand relationships, and we can search images better," said Aarabi.
The nimble algorithm, called relational social image search, achieves high reliability without using computationally intensive object - or facial-recognition software.
"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," said Aarabi.
Work on this project began in 2005 in Aarabi's Mobile Applications Lab, Canada's first lab space for mobile application development.
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," said Aarabi.
While testing the algorithm, Aarabi and Appel discovered an unforeseen application: a new way to generate maps.
They tagged a few photographs of buildings around the university campus 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," said Aarabi.