As concerns grow about the ability of computers to track children and their activities into their adult lives, questions emerge about whether facial recognition technology could recognize an adult based on images of that person as a child.
University of Kent forensic researcher Stuart Gibson says facial recognition systems would have difficulty matching an image of a child under the age of seven with that same person as an adult, because of the way in which the face changes beginning at age seven.
Gibson developed computer models that attempt to artificially age images of children at different ages. His attempts to quantitatively model changes in bone structure, skin texture, and other variables could improve facial recognition technology.
University of California, Los Angeles professor Stefano Soatto believes studies of aging and facial recognition could benefit from his paper on eliminating variability with respect to focal length in images, which heavily distorts faces. Researchers could enter numerous images into the model and "learn away the variability," Soatto says. Variability includes actual changes in a person's face over time, as well as "nuisance variability," or image features that are irrelevant to identity.
Experts believe research on facial recognition and aging will increase as social networks acquire thousands of images of an individual over a period of time.
From The Atlantic
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