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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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DOI (Published version): 10.1111/j.1467-8659.2008.01158.x

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
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URI: https://cronfa.swan.ac.uk/Record/cronfa5277
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first_indexed 2013-07-23T11:52:10Z
last_indexed 2018-02-09T04:31:27Z
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spelling 2013-11-05T13:01:06.9109724 v2 5277 2012-02-23 Image-based Aging Using Evolutionary Computing a5c03d2fcd1e4a881ced4d33bb206c95 Min Chen Min Chen true false 3c75caf0df70504d841270d636835fde Philip Grant Philip Grant true false 2012-02-23 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. Journal Article Computer Graphics Forum 27 2 607 616 0167-7055 1467-8659 31 12 2008 2008-12-31 10.1111/j.1467-8659.2008.01158.x COLLEGE NANME COLLEGE CODE Swansea University 2013-11-05T13:01:06.9109724 2012-02-23T17:01:47.0000000 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Daniel Hubball 1 Min Chen 2 Phil W Grant 3 Philip Grant 4
title Image-based Aging Using Evolutionary Computing
spellingShingle Image-based Aging Using Evolutionary Computing
Min Chen
Philip Grant
title_short Image-based Aging Using Evolutionary Computing
title_full Image-based Aging Using Evolutionary Computing
title_fullStr Image-based Aging Using Evolutionary Computing
title_full_unstemmed Image-based Aging Using Evolutionary Computing
title_sort Image-based Aging Using Evolutionary Computing
author_id_str_mv a5c03d2fcd1e4a881ced4d33bb206c95
3c75caf0df70504d841270d636835fde
author_id_fullname_str_mv a5c03d2fcd1e4a881ced4d33bb206c95_***_Min Chen
3c75caf0df70504d841270d636835fde_***_Philip Grant
author Min Chen
Philip Grant
author2 Daniel Hubball
Min Chen
Phil W Grant
Philip Grant
format Journal article
container_title Computer Graphics Forum
container_volume 27
container_issue 2
container_start_page 607
publishDate 2008
institution Swansea University
issn 0167-7055
1467-8659
doi_str_mv 10.1111/j.1467-8659.2008.01158.x
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
active_str 0
description 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.
published_date 2008-12-31T03:06:19Z
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score 11.013731

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