Photo Tagging, And Sneaky Algorithms

A new algorithm designed at the University of Toronto could change the way we find photos among the billions on social media sites such as Facebook and Flickr.

Developed by Parham Aarabi, a professor in The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, and his former Master’s student Ron Appel, the search tool uses the locations of tagged persons to quantify relationships between them, 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.

“Two things are happening: we understand relationships, and we can search images better,” says Professor Aarabi.

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

Read the rest of "New Algorithm Finds You, Even In Untagged Photos" at KurzweilAI.net


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