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Researchers bypass facial recognition by building social networks from photo tags

on December 3, 2013

Gigaom

University of Toronto researchers have developed an algorithm for predicting the identity of untagged people in photos by analyzing their relationships to other people in the photos. The process is kind of like creating a social network for tags, a process the creators claim could minimize the need for running computationally intensive facial-recognition algorithms to auto-tags photos.

So, the algorithm might predict, for example, that the third person in a photo of me and my wife is our daughter — assuming she has been tagged before and there’s a sufficient volume of tagged images of everyone involved to allow the algorithm to accurately weigh the strengths of our relationships in any given group. That’s why although this is an interesting concept, it might be of limited utility in commercial applications.

 

In academia, researchers are more likely to thoroughly tag photos in order to ensure the accuracy of their work. In…

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