Prince George may still only be a toddler but computer scientists say they can now offer a glimpse of how the third in line to the British throne will look in the coming years.
Their new software takes a number of specific facial features and combines it with visual cues from the parents and other relatives to create a detailed portrait of an individual’s likely future appearance. The results are far more accurate than existing ‘ageing’ software, say the scientists from the University of Bradford.
The research, led by Hassan Ugail, the University’s Professor of Visual Computing, explained that their algorithm can verify which traits the child may have inherited from the parents to build a more reliable forecast of their future face. He said that the software is ‘trained’ to be more accurate as further layers of data are added.
To demonstrate the system the team chose to predict what Prince George will look like over the coming years, up until the year 2073 when he’ll celebrate his 60th birthday.
“We take specific facial features. Very simple things like nose length is quite unique for that person, so we look at nose length, the width of the nose, the distance between eyes. So these are facial features that the computer recognizes as the person. So we take these - roughly 30 to 40 facial features we take from the face - and we use these facial features; we map it into the machine and then we produce the age,” Professor Ugail told Reuters.
“So what we’ve done in the case of George, we’ve taken his picture and then we’ve actually taken facial features and then aged him. We’ve also, in some experiments, what we’ve done is we’ve taken the parental information and then also applied the parental information and aged him as well.”
The team also created portraits of Prince George’s little sister, Princess Charlotte, ageing her from the age of two up until age 60.
Ugail explained how the system assumes a ‘natural age progression’; not taking into account the impact of factors like diet and environment. Nevertheless, he believes that the program’s facial predictions offer an accuracy of around eighty per cent.
“It’s very, very difficult to 100 percent say this is what the person is going to look like because there are other things that come into it. You know, there’s environmental issues, there are dieting habits. So all these things can age people very fast. So it’s very, very difficult to predict it, but what we assume is a natural age progression. So from that point of view our software is roughly 80 percent accurate,” he said, adding that the hair styles on their images were purely for illustration.
Only time will tell just how accurate the team’s predictions are. But Ugail says they’ve built in safeguards that test their images’ accuracy.
“We make sure for a given picture, for a given image, that it actually passes a face recognition test. So what it means, is like if I were to age you from where you are now to, say, ten years ahead; we’d take your current picture, your current facial features and we’ll pass it through a face recognition test. And then we also make sure that our predicted picture also passes through a face recognition test.”
The team has been approached about making the software into an app. While Ugail admits there is a fun side to the system, he’s keen to highlight its potential in police investigations. Originally, it was developed to identify criminal suspects in crowds, and Ugail believes it could be an important tool to help trace missing children and adults.
“We can actually look at a child’s pictures, we can incorporate all the pictures available, we can also add information from parents, parental facial features, grandparental facial features if available and also other relatives in the family. So we can take all that information so the accuracy that we can predict would be much, much better compared to the current existing technology,” said Ugail.