Illumination-Aware Age Progression
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DescriptionWe present an approach that takes a single photograph of a child as input and automatically produces a series of age-progressed outputs between 1 and 80 years of age, accounting for pose, expression, and illumination. Leveraging thousands of photos of children and adults at many ages from the Internet, we first show how to compute average image subspaces that are pixel-to-pixel aligned and model variable lighting. These averages depict a prototype man and woman aging from 0 to 80, under any desired illumination, and capture the differences in shape and texture between ages. Applying these differences to a new photo yields an age progressed result. Contributions include relightable age subspaces, a novel technique for subspace-to-subspace alignment, and the most extensive evaluation of age progression techniques in the literature.
Read and watch more: paper, sup. material, results, youtube video, episode on CBS.
For follow up work: cite, FGNET dataset by Lanitis, htmls for MTurk, results on the full FGNET.
ResultsFor each example, we show the input (left) and automatically "aged" version of the input using our method (right). Age is specified below each photo.
ComparisonA single photo of a child (far left) is age progressed (left in each pair) and compared to photos of the same person at the corresponding age (right in each pair). The age progressed face is composited into the ground truth photo to match the hairstyle and background (see supplementary material for comparisons of just the face regions).
MorphsVideo on YouTube
Left image is the starting input photo, and right image will transform to age 80 to show our automatic aging process.
AcknowledgementsWe thank Google and Intel for supporting this research and "Thunder" for allowing us to use his photo collection for comparisons.
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ContactFor more information please contact @kemelmi: Ira Kemelmacher-Shlizerman