Social networks like Facebook may soon be able to tell which urban tribe you belong to. University of California, San Diego computer scientists are developing an algorithm that uses group pictures to determine whether you’re a hipster, Goth, biker, or surfer. So far, the algorithm is about 5 times more accurate than chance, but the researchers think they can get it to perform at least as well as a human.
Researcher Serge Belongie said identifying urban tribes is surprisingly difficult for computers. To tackle the task, Belongie’s team worked with pictures of the eight most popular subcultures: biker, country, Goth, heavy metal, hip hop, hipster, raver, and surfer. One of the team’s insights was to analyze group pictures rather than pictures of individuals. They hoped that this would make it easier to pick up social cues – such as clothing and hairdos – to determine people’s tribes based on visuals featuring more than one person.
Specifically, the algorithm segments each person into six sections – face, head, top of the head (where a hat would be), neck, torso, and arms. The algorithm then analyzes the picture as the sum of its parts and attributes – in this case haircuts, hair color, make up, jewelry, and tattoos. The algorithm also analyzes the sections for color, texture and other factors.
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