A Toothy Grin or Angry Snarl Makes It Easy to Stand Out in a Crowd: New Study Finds Visible Teeth Are Key to Identifying a Face in a Large Group

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Citations Journal of Vision (doi: 10.1167/12.5.7)

Newswise — Rockville, Md. – Scientists have found new evidence that people spot a face in the crowd more quickly when teeth are visible — whether smiling or grimacing — than a face with a particular facial expression. The new findings, published in the Journal of Vision, counters the long held “face-in -the-crowd” effect that suggests only angry looking faces are detected more readily in a crowd.

“The research concerned with the face-in-the-crowd effect essentially deals with the question of how we detect social signals of friendly or unfriendly intent in the human face,” said author Gernot Horstmann, PhD, of the Center for Interdisciplinary Research and Department of Psychology at Bielefeld University, Germany. “Our results indicate that, contrary to previous assertions, detection of smiles or frowns is relatively slow in crowds of neutral faces, whereas toothy grins and snarls are quite easily detected.”

In two studies, the researchers asked subjects to search for a happy or an angry face within a crowd of neutral faces, and measured the search speed. While the search was relatively slow when emotion was signaled with a closed mouth face, the speed search doubled when emotion was signaled with an open mouth and visible teeth. This was the case for both happy and angry faces, and happy faces were found even somewhat faster than angry faces.

Horstmann and his colleagues conducted these experiments as a result of discrepancies in previous studies that investigated visual search for emotional faces. According to the research team, the inconsistent results with respect to which of the two expressions are found faster — the happy face or the angry face — suggested that the emotional expression category could not be the only important factor determining the face-in- the-crowd effect.

The scientists believe this new study may explain the discrepancies. “This will probably inspire researchers to clarify whether emotion and, in particular, threat plays an additional, unique role in face detection,” said Horstmann.

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ARVO’s Journal of Vision (www.journalofvision.org) is an online-only, peer-reviewed, open-access publication devoted to visual function in humans and animals. It explores topics such as spatial vision, perception, low vision, color vision and more, spanning the fields of neuroscience, psychology and psychophysics. JOV is known for hands-on datasets and models that users can manipulate online.

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