This technique leverages the average of thousands of faces of the same age and gender, then calculates the visual changes between groups as they age to apply those changes to a new person's face. The shape and appearance of a baby's face - and variety of expressions - often change drastically by adulthood, making it hard to model and predict that change. The research team has posted a paper on the new technique and will present its findings at the June IEEE Computer Vision and Pattern Recognition conference in Columbus, Ohio. "We took photos of children in completely unrestrained conditions and found that our method works remarkably well." "Aging photos of very young children from a single photo is considered the most difficult of all scenarios, so we wanted to focus specifically on this very challenging case," said Ira Kemelmacher-Shlizerman, a UW assistant professor of computer science and engineering. The technique is the first fully automated approach for aging babies to adults that works with variable lighting, expressions and poses. University of Washington researchers have developed software that automatically generates images of a young child's face as it ages through a lifetime.
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