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Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation
Hongyu Yang1; Di Huang1; Yunhong Wang1; Heng Wang1; Yuanyan Tang2
2016-06-01
Source PublicationIEEE Transactions on Image Processing
ISSN1057-7149
Volume25Issue:6Pages:2493-2507
Abstract

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time. It then transforms the age component to a target age group via sparse reconstruction, yielding aging effects, which is finally combined with the identity component to achieve the aged face. Experiments are carried out on three face aging databases, and the results achieved clearly demonstrate the effectiveness and robustness of the proposed method in rendering a face with aging effects. In addition, a series of evaluations prove its validity with respect to identity preservation and aging effect generation.

KeywordFace Aging Simulation/progression/synthesis Hidden Factor Analysis Sparse Representation
DOIhttps://doi.org/10.1109/TIP.2016.2547587
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000374890600006
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Fulltext Access
Citation statistics
Cited Times [WOS]:23   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorHongyu Yang; Di Huang; Yunhong Wang; Heng Wang; Yuanyan Tang
Affiliation1.Laboratory of Intelligent Recognition and Image Processing, the Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, China
2.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa 853, Macau
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Hongyu Yang,Di Huang,Yunhong Wang,et al. Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation[J]. IEEE Transactions on Image Processing,2016,25(6):2493-2507.
APA Hongyu Yang,Di Huang,Yunhong Wang,Heng Wang,&Yuanyan Tang.(2016).Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.IEEE Transactions on Image Processing,25(6),2493-2507.
MLA Hongyu Yang,et al."Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation".IEEE Transactions on Image Processing 25.6(2016):2493-2507.
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