NDLI: A Compositional and Dynamic Model for Face Aging

Content Provider	IEEE Xplore Digital Library
Author	Jinli Suo Song-Chun Zhu Shiguang Shan Xilin Chen
Copyright Year	1979
Abstract	In this paper, we present a compositional and dynamic model for face aging. The compositional model represents faces in each age group by a hierarchical And-or graph, in which And nodes decompose a face into parts to describe details (e.g., hair, wrinkles, etc.) crucial for age perception and Or nodes represent large diversity of faces by alternative selections. Then a face instance is a transverse of the And-or graph-parse graph. Face aging is modeled as a Markov process on the parse graph representation. We learn the parameters of the dynamic model from a large annotated face data set and the stochasticity of face aging is modeled in the dynamics explicitly. Based on this model, we propose a face aging simulation and prediction algorithm. Inversely, an automatic age estimation algorithm is also developed under this representation. We study two criteria to evaluate the aging results using human perception experiments: (1) the accuracy of simulation: whether the aged faces are perceived of the intended age group, and (2) preservation of identity: whether the aged faces are perceived as the same person. Quantitative statistical analysis validates the performance of our aging model and age estimation algorithm.
Sponsorship	IEEE Computer Society
Page Count	17
File Size	4757452
Starting Page	385
Ending Page	401
File Format	PDF
ISSN	01628828
Volume Number	32
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Aging Face detection Hair Predictive models Humans Face recognition Shape Biological system modeling Computational modeling Computer simulation ANOVA. Face aging modeling face age estimation generative model And-Or graph
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Age-Invariant Face Recognition

A Concatenational Graph Evolution Aging Model

Detection and analysis of hair

Automatic Age Estimation Based on Facial Aging Patterns

Age Synthesis and Estimation via Faces: A Survey

Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model

Face detection from color images using a fuzzy pattern matching method

Example-based learning for view-based human face detection

Recovering Facial Shape Using a Statistical Model of Surface Normal Direction

A Compositional and Dynamic Model for Face Aging

Similar Documents

Age-Invariant Face Recognition

A Concatenational Graph Evolution Aging Model

Detection and analysis of hair

Automatic Age Estimation Based on Facial Aging Patterns

Age Synthesis and Estimation via Faces: A Survey

Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model

Face detection from color images using a fuzzy pattern matching method

Example-based learning for view-based human face detection

Recovering Facial Shape Using a Statistical Model of Surface Normal Direction

A Compositional and Dynamic Model for Face Aging