Washington: Engineers from the University of Toronto have developed a new algorithm that could potentially change and simplify the way we look for pics among the billions on social media sites.
Developed by Parham Aarabi, a professor in The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, and his former student, Ron Appel, the search tool 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.
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.
The nimble algorithm, called relational social image search, achieves high reliability without using computationally intensive object or facial recognition software.
Aarabi said that Facebook has almost half a trillion photos, but a billion users and their 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.
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.
