Sure, it can be difficult to feel like smiling while getting your photo taken on a trip to renew your passport or license.
Although natural smiles that don’t exaggerate or hide facial features are allowed, the preferred passport photo is one with a completely neutral expression and both eyes open.
However, a new study has found that showcasing a big smile in an ID photo could make it easier to correctly identify you and even prevent identity fraud.
Researchers from the University of York conducted the study to examine how smiles in photos affect accurate identification. Previous research has shown a wide gap of human error in correctly matching a human face to a photo.
Even smartphones that have face unlocking capabilities can be tricked by face-morphing technology.
The researchers decided to test if smiles could make photo recognition easier with three different studies.
“Photo ID is a significant part of our lives and yet we know that the human brain has a hard time matching photos of people to other photos and matching photos with the real-life person,” said Mila Mileva. “Identity fraud is a real problem on many levels, so it is important that we do more research in this area to see how we can improve methods of identification.”
For two of the studies, 40 participants were given 60 images of neutral facial expressions and were asked to match the images to an open-mouth smiling face or a closed smiling face.
In the third study, 34 participants had to match photos of people with just the lower part of the face visible.
The researchers found that open-mouthed or wide smiles made matching photos easier in all three studies.
“Our research suggests that replacing the neutral expression we usually use when taking identification photographs with an open mouth smile, can make face matching an easier decision,” said Mileva. “As soon as there’s a mismatch in emotional expression – comparing a smiling and a neutral image for example – the matching accuracy drops substantially.”
Smiling in photos also made it easier for participants to identify people who looked alike but weren’t the same, which could be helpful in preventing future identity fraud.