Image-based Aging Using Evolutionary Computing

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Date
2008
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd
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.
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@article{
10.1111:j.1467-8659.2008.01158.x
, journal = {Computer Graphics Forum}, title = {{
Image-based Aging Using Evolutionary Computing
}}, author = {
Hubball, Daniel
and
Chen, Min
and
Grant, Phil W.
}, year = {
2008
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd
}, ISSN = {
1467-8659
}, DOI = {
10.1111/j.1467-8659.2008.01158.x
} }
Citation