Since 2010, Facebook has used facial recognition software to automatically tag your friends in photos. Now one researcher has come up with an algorithm that tags photos based on the relationships that people in images already have with each other.
The algorithm uses the name and location of existing photo tags to build a "relationship graph," where personal connections in the images are calculated. That makes it faster and more efficient at tagging pictures compared to what's currently used by sites such as Facebook and Flickr.
For example, if a father and daughter appear in tagged images consistently, untagged photos featuring them can be tagged automatically. If the daughter is in an image with both of her parents, but the father is untagged, the algorithm is able to recognize him based on their other images together.
See also: Facebook Turns On Facial Recognition For Tagging By Default
University of Toronto engineering professor Parham Aarabi has been working on the technology since 2005. He emphasizes the advantages of the algorithm over Facebook's face-recognition photo tagging system.
"The goal of face recognition is to find or generate a new tag when there is none," Aarabi told Mashable. "By using the tag locations and generating a relationship graph, we are essentially extracting the meaning from photos without significant computational analysis — since we only analyze the name and location of a particular tag, not the pixels of the entire image." 
Aarabi has not yet been in touch with Facebook or other photo sharing sites about the algorithm technology. It will be patented by the United States Patent and Trademark Office on Dec. 17.
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Image: iStock, Lightguard