Lying about your age? A computer can tell

Facing the signs of aging
Huang’s group approached the general aging problem with a “black box” approach that relied on computer algorithms to establish connections among people of the same or similar ages. For one study, an algorithm divided each face into 10,000 pixels and asked which pixels clustered among people of the same age group. Another algorithm looked for similarities and differences in the geometry of key facial features, and a third measured texture as a way to quantify the amount of age-related wrinkling.

In two separate papers, published earlier this year in the journals IEEE Transactions on Multimedia and IEEE Transactions on Image Processing, Huang and his colleagues trained and tested separate algorithm combinations primarily on a database of 1,600 individuals ranging in age from 1 to 93 (each person was represented by five pictures taken around the same time, for a total of 8,000 images).

The programs’ guesswork on new faces, while besting other available techniques, has been far from infallible. So far, Huang said, the software can accurately estimate age to within five years only half the time, though it correctly assigns ages to within a decade about 80 percent of the time. For one face shot of Albert Einstein taken when he was 33, the computer model was right on the money, while another estimate of his age when he was 55 was off by 15 years.

Huang said his group is refining the two algorithm approaches and hopes to improve their accuracy by training both on far larger databases, like the MORPH archive of 55,000 faces from 13,000 people maintained at the University of North Carolina at Wilmington.

Even the primary morphological mechanisms behind aging have been difficult to discern, said Ricanek, whose group manages the MORPH database. In children, the apparent aging process is mediated primarily by skeletal growth and development, while in adults, changes in soft, non-bony tissues predominate.

“If we lived in an ideal world — a perfect world — the only effects would be from our genes and gravity,” Huang said.

Effects of aging
But in the real world, aging can be easily affected by behavior as simple as raising your eyebrows. Over time, raising your brows gradually creates what are known to scientists as hyperdynamic facial lines in your forehead (wrinkles for the rest of us). Younger, more elastic skin can erase the creases, but after a while, older adults are stuck with the kinds of laugh lines, crow’s feet and yes, forehead folds that have sent celebrities running for their Botox injections.

Similarly, photoaging, or sun exposure, can begin to crack and crease someone’s skin as if it was a cowhide left out in the sun. Tanning while taking some prescription drugs can lead to even faster photoaging.

Ricanek is developing models to simulate the aging process and produce images of how someone might look 20 years later, though like Huang, he has based his research on estimating someone’s apparent rather than actual age. He figures his group’s methods can estimate age to within four or five years of the truth more than half the time, but he cautioned that his analysis cannot be directly compared with Huang’s methods.

As age-verification applications become more prevalent, privacy concerns are bound to spring up, though Ricanek and Huang both said computer software can address those concerns by capturing only data on gender and age and not the individual’s identity.

Consumers in the U.S. may still have some time to get used to the idea. For an age-identification system to be reliably used for something like detecting underage drinkers, Ricanek estimated it would need to have no more than one false alarm per every 100,000 tries — a success rate he believes will require a decade or so to achieve.

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