Do you have a forgettable face?
Many of us go to great lengths to make our faces more memorable, using makeup
and hairstyles to give ourselves a more distinctive look. Now your face could
be instantly transformed into a more memorable one without the need for an
expensive makeover, thanks to an algorithm developed by researchers in MIT’s
Computer Science and Artificial Intelligence Laboratory (CSAIL). The algorithm,
which makes subtle changes to various points on the face to make it more
memorable without changing a person’s overall appearance, was unveiled earlier
this month at the International Conference on Computer Vision in Sydney. The
system could ultimately be used in a smartphone app to allow people to modify a
digital image of their face before uploading it to their social networking
pages. It could also be used for job applications, to create a digital version
of an applicant’s face that will more readily stick in the minds of potential
employers. Conversely, it could also be used to make faces appear less
memorable, so that actors in the background of a television program or film do
not distract viewers’ attention from the main actors, for example. To develop
the memorability algorithm, the team first fed the software a database of more
than 2,000 images.
Each of these images had been
awarded a ‘memorability score’, based on the ability of human volunteers to
remember the pictures. In this way the software was able to analyze the
information to detect subtle trends in the features of these faces that made
them more or less memorable to people. The researchers then programmed the
algorithm to make the face as memorable as possible, but without changing the
identity of the person or altering their facial attributes, such as their age,
gender, or overall attractiveness. Changing the width of a nose may make a face
look much more distinctive, for example, but it could also completely alter how
attractive the person is, and so would fail to meet the algorithm’s objectives.
When the system has a new face to modify, it first takes the image and
generates thousands of copies. Each of these copies contains tiny modifications
to different parts of the face. The algorithm then analyzes how well each of
these samples meets its objectives. Once the algorithm finds a copy that
succeeds in making the face look more memorable without significantly altering
the person’s appearance, it makes yet more copies of this new image, with each
containing further alterations. It then keeps repeating this process until it
finds a version that best meets its objectives.
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