Skip to main navigation Skip to search Skip to main content

Modeling age progression in young faces

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a craniofacial growth model that characterizes growth related shape variations observed in human faces during formative years. The model draws inspiration from the 'revised' cardioidal strain transformation model proposed in psychophysical studies related to craniofacial growth. The model takes into account anthropometric evidences collected on facial growth and hence is in accordance with the observed growth patterns in human faces across years. We characterize facial growth by means of growth parameters defined over facial landmarks often used in anthropometric studies. We illustrate how the age-based anthropometric constraints on facial proportions translate into linear and non-linear constraints on facial growth parameters and propose methods to compute the optimal growth parameters. The proposed craniofacial growth model can be used to predict one's appearance across years and to perform face recognition across age progression. This is demonstrated on a database of age separated face images of individuals under 18 years of age.

Original languageEnglish (US)
Title of host publicationProceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Pages387-394
Number of pages8
DOIs
StatePublished - 2006
Externally publishedYes
Event2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 - New York, NY, United States
Duration: Jun 17 2006Jun 22 2006

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1
ISSN (Print)1063-6919

Other

Other2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Country/TerritoryUnited States
CityNew York, NY
Period6/17/066/22/06

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Modeling age progression in young faces'. Together they form a unique fingerprint.

Cite this