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Image-based Aging Using Evolutionary Computing

Daniel Hubball, Min Chen, Phil W Grant, Philip Grant

Computer Graphics Forum, Volume: 27, Issue: 2, Pages: 607 - 616

Swansea University Authors: Min Chen , Philip Grant

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Abstract

Aging has considerable visual effects on the human face and is difficult to simulate using a universally-applicable global model. In this paper, we focus on the hypothesis that the patterns of age progression (and regression) are related to the face concerned, as the latter implicitly captures the c...

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Published in: Computer Graphics Forum
ISSN: 0167-7055 1467-8659
Published: 2008
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa5277
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Abstract: Aging has considerable visual effects on the human face and is difficult to simulate using a universally-applicable global model. In this paper, we focus on the hypothesis that the patterns of age progression (and regression) are related to the face concerned, as the latter implicitly captures the characteristics of gender, ethnic origin, and age group, as well as possibly the person-specific development patterns of the individual. We use a data-driven framework for automatic image-based facial transformation in conjunction with a database of facial images. We build a novel parameterized model for encoding age-transformation in addition with the traditional model for face description. We utilize evolutionary computing to learn the relationship between the two models. To support this work, we also developed a new image warping algorithm based on non-uniform radial basis functions (NURBFs). Evolutionary computing was also used to handle the large parameter space associated with NURBFs. In comparison with several different methods, it consistently provides the best results against the ground truth.
College: College of Science
Issue: 2
Start Page: 607
End Page: 616