Illumination-Aware Age Progression

CVPR 2014

Ira Kemelmacher-Shlizerman, Supasorn Suwajanakorn, Steven M. Seitz



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Abstract | Download | Results | Popular press | Bibtex | Contact | more project videos

Abstract

Example Results , see data and files for comparison below.
CBS Innovation nation did a great episode about our software: check it out here!; full episode.

We 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.



Files

Paper: pdf appeared at IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2014
Citation to the paper at google scholar: bibtex
Additional results and experiments: pdf
Video: YouTube
The FGNET Database that we used for comparisons: FGNET zip by Andreas Lanitis
Htmls of our Amazon Mechanical Turk tasks used for evaluation: Htmls for Mechanical Turk.
Our results on all the FGNET photos: FGNET age progression results (193Mb)
Please let us know if you compare to our results, and cite the paper.

Results

Below are many examples of our automatic age progression. For each example, we show the input (left) and automatically "aged" version of the input using our method (right). Age is specified below each photo.

Males:

Females:

Comparison

A 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).

Morphs

Video on YouTube

Left image is the starting input photo, and right image will transform to age 80 to show our automatic aging process.
Age 1 Age 2 Age 3 Age 3

Acknowledgements

We thank Google and Intel for supporting this research and "Thunder" for allowing us to use his photo collection for comparisons.

Popular press:

The Seattle Times | UW news | CSE news | Ars Technica | GeekWire | Gizmodo | Gizmag | Telegraph UK | IEEE Spectrum | PetaPixel | DailyMail UK | Independent UK | Popular Science | חורים ברשת | Wired UK | Ynet | NBC Today | Shape
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BibTex

Contact

For more information please contact @kemelmi: Ira Kemelmacher-Shlizerman

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