Title
Illumination-Aware Age Progression
Abstract
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.
Year
DOI
Venue
2014
10.1109/CVPR.2014.426
Computer Vision and Pattern Recognition
Keywords
Field
DocType
Internet,age issues,image processing,lighting,photography,pose estimation,prototypes,Internet,average image subspaces,child photograph,illumination-aware age progression technique,pixel-to-pixel aligned subspaces,prototype woman aging,relightable age subspaces,subspace-to-subspace alignment,variable lighting model,age,automatic,computer vision,faces,lighting,optical flow,progression,synthesis
Age progression,Computer vision,Pattern recognition,Computer science,Linear subspace,Artificial intelligence,Optical flow,The Internet
Conference
ISSN
Citations 
PageRank 
1063-6919
59
1.95
References 
Authors
19
3
Name
Order
Citations
PageRank
Ira Kemelmacher-Shlizerman171028.03
Supasorn Suwajanakorn226611.20
Steven M. Seitz38729495.13