i think you will all agree that when you look at someone and find the person attractive you
cannot explain why there are many reasons involved in this decision
plus some of these reasons may not even be directly related to the physique of the person
still when you look at a picture of someone you instantly know if the person is attractive or not
by your standards and you know this without any doubts but how does that happen can we explain
or understand what beauty is to us and worse can someone else understand what we find beautiful is
beauty even something universal or subjective to me it's definitely something subjective
just like art as we say beauty is in the eye of the beholder isn't it but then why specific
people become actors or models and not others is there a universal beauty that we could explain
is beauty something cultural biological or a blend of both i think these are mostly philosophical
debates that we can discuss in the comments for those of you that will like to i would love to
chat and even debate about this with you anyways back to what we know about beauty as we know
humans typically respond emotionally to attractive images rather than purely based
on rational visually salient reasons which is what makes beauty so subjective but is there a
way to understand what we think of beauty and use this information to create attractive pictures
can we understand our brain signals to achieve that and is it even readable to these signals well
this is what michel spape and his team from the university of helsinki attempted to do what you
see here is called electroencephalography or eeg it's a monitoring method used to record electrical
brain activity using electrodes placed along the scalp specifically they tracked two different
channels with these electrodes which are known to be responsive to stimuli that are either novel or
effectively evocative or mentally demanding and related to working memory updating meaning that
the stimuli are improbable and require a mental or physical response but they employed two strategies
in their experiments first they made the supposed attractive images relatively improbable to appear
they also asked the participants to focus on attractive faces by mentally counting
their occurrence to me these strategies seem like a considerable bias to detecting actual
attractiveness where the signal responses mainly tell us two things one that the person is lightly
surprised because the attractive pictures are rare and two that the person is mentally active trying
to remember the count and add to it i personally see it as an overkill way of asking whether the
person finds the face attractive or not since it does not really measure the beauty of the image
scene and here i am not entering about the details of the data set they used to train their model
which is only made of celebrities nonetheless this was undoubtedly a great way to find out
which faces were attractive or not to train their model to focus on beautiful faces which is a very
cool application of guns as you can see it clearly worked out there's a significant difference
between responses after a slight delay of time starting approximately a fourth of a second after
showing the image where the pink lines are the two channel responses i just mentioned are shown here
the top shows the frontal response responsible for the novel and effectively evocative stimuli
while the bottom is the parietal response responsible for mentally demanding stimuli here
the faces deemed attractive are green unattractive in red and inconsistent responses in gray these
inconsistent responses signified that the data was not used due to its low level of confidence
attractiveness was confident when both electrodes evoked more positivity for the attractive faces
now let's see how they created such a model to use their brain activity to generate attractive faces
at first they needed to generate random images to show the test subjects to do that they used
a gun model trained on 200 000 images of celebrity faces already introducing a bias but still let's
keep going they then had a latent space from which they could use to generate new artificial images
this is just like any other gun model like deep fakes it is very similar to what i
already explained in previous videos and you are most certainly aware of how it works so i won't
cover it again here but if you are not you are free to click on the top right pop-up and watch
my explanations of gan architectures and i'll talk a little bit more about this latent space
later on then each participant was asked to go through randomly generated images remember here
they had to count when they see an attractive face mentally once the results are all compiled
they train a classifier on these brain output signals containing the image's subject assessments
basically ideally containing whether the face was attractive or not
once the classifier is trained it's used under brain electrical responses on randomly generated
images note that all these randomly generated images come from a latent space originally
created by the encoder of the gun trained on the first step as you can see here the latent space
is a space where one point represents an input the generator can use to create a unique image
this space contains all the faces that this generator can make
thus when an image is generated using a point in the space or feature vector it can be considered
attractive or not by the classifier if that's the case it will encourage the network to create
images by selecting the generator's input close to this point in the space focusing the generator's
attention on a subspace where the features of the generated faces are pleasing to the participant
finally this is how new images containing optimal values for personal attractive features on a
human face are generated i hope you enjoyed this video and i definitely invite you to read their
paper it's very interesting and well written it's the first link in the description don't
forget to like and subscribe if you enjoyed the video and share your thoughts in the comments
where i will answer you in the following 7 minutes i promise thank you for watching
you