Care To Try The ‘Beauty Machine’?
Beauty is in the eye of the beholder. This saying first appeared in the 3rd century BC in Greek. It didn’t appear in its current form in print until the 19th century, but in the meantime there were various written forms that expressed much the same thought. In 1588, the English dramatist John Lyly, in his Euphues and his England, wrote:
“…as neere is Fancie to Beautie, as the pricke to the Rose, as the stalke to the rynde, as the earth to the roote.”
Shakespeare expressed a similar sentiment in Love’s Labours Lost, 1588:
Good Lord Boyet, my beauty, though but mean,
Needs not the painted flourish of your praise:
Beauty is bought by judgement of the eye,
Not utter’d by base sale of chapmen’s tongues
Benjamin Franklin, in Poor Richard’s Almanack, 1741, wrote:
Beauty, like supreme dominion
Is but supported by opinion
beauty is in the eye of the beholderDavid Hume’s Essays, Moral and Political, 1742, include:
“Beauty in things exists merely in the mind which contemplates them.”
The person who is widely credited with coining the saying in its current form is Margaret Wolfe Hungerford (née Hamilton), who wrote many books, often under the pseudonym of ‘The Duchess’. In Molly Bawn, 1878, there’s the line “Beauty is in the eye of the beholder”, which is the earliest citation of it that I can find in print.
But researchers from Tel Aviv University are now challenging the adage.
They’ve built a beauty machine that, with the press of a button, turns a picture of your own ordinary face into that of a cover model. While its output is currently limited to digitized images, the software may be able to guide plastic surgeons, aid magazine cover editors, and even become a feature incorporated into all digital cameras.
“Beauty, contrary to what most people think, is not simply in the eye of the beholder,” says lead researcher Prof. Daniel Cohen-Or of the Blavatnik School of Computer Sciences at Tel Aviv University. With the aid of computers, attractiveness can be objectified and boiled down to a function of mathematical distances or ratios, he says. This function is the basis for his beauty machine.
In the Eyes of a Majority of Beholders
The research has attracted interest and controversy. Beauty is, after all, a quality that has captivated artists since time immemorial, and its definition has eluded even the world’s greatest philosophers. Prof. Cohen-Or sees things more scientifically.
“Beauty can be quantified by mathematical measurements and ratios. It can be defined as average distances between features, which a majority of people agree are the most beautiful,” says Prof. Cohen-Or. “I don’t claim to know much about beauty. For us, every picture in this research project is just a collection of numbers.”
In his study, published recently in the proceedings of Siggraph, an annual computer graphics conference, Prof. Cohen-Or and his graduate student Tommer Leyvand together with two colleagues surveyed 68 Israeli and German men and women, aged 25 to 40, asking them to rank the beauty of 93 different men’s and women’s faces on a scale of 1 to 7. These scores were then entered into a database and correlated to 250 different measurements and facial features, such as ratios of the nose, chin and distance from ears to eyes. From this, the scientists created an algorithm that applies desirable elements of attractiveness to a fresh image.
True to the Real You
Unlike heavily processed Photoshop images that can make magazine cover models and celebrities unrecognizable, Tel Aviv University’s “beautification engine” is much more subtle. Observers say that the final image it produces retains an unmistakable similarity to the original picture.
Well — in most cases. There is one circumstance where Prof. Cohen-Or’s beauty machine doesn’t work like a charm: when a celebrity’s face is changed.
“We’ve run the faces of people like Brigitte Bardot and Woody Allen through the machine and most people are very unhappy with the results,” he admits. “But in unfamiliar faces, most would agree the output is better.” Prof. Cohen-Or now plans on developing the beauty machine further — to add the third dimension of depth.
ACM SIGGRAPH 2008
Data-Driven Enhancement of Facial Attractiveness
Tommer Leyvand, Daniel Cohen-Or, Gideon Dror and Dani Lischinski
When human raters are presented with a collection of shapes and asked to rank them according to their aesthetic appeal, the results
often indicate that there is a statistical consensus among the raters. Yet it might be difficult to define a succinct set of rules that capture the aesthetic preferences of the raters. In this work, we explore a data-driven approach to aesthetic enhancement of such shapes. Specifically, we focus on the challenging problem of enhancing the aesthetic appeal (or the attractiveness) of human faces in frontal photographs (portraits), while maintaining close similarity with the original.
The key component in our approach is an automatic facial attractiveness engine trained on datasets of faces with accompanying facial attractiveness ratings collected from groups of human raters. Given a new face, we extract a set of distances between a variety of facial feature locations, which define a point in a high-dimensional “face space”. We then search the face space for a nearby point with a higher predicted attractiveness rating. Once such a point is found, the corresponding facial distances are embedded in the plane and serve as a target to define a 2D warp field which maps the original facial features to their adjusted locations. The effectiveness of our technique was experimentally validated by independent rating experiments, which indicate that it is indeed capable of increasing the facial attractiveness of most portraits that we have experimented with.