Estimating human age by manifold analysis of face pictures and regression on aging features

Yun Fu, Ye Xu, Thomas S. Huang

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

Abstract

Extensive recent studies on human faces reveal significant potential applications of automatic age estimation via face image analysis. Due to the temporal features of age progression, aging face images display sequential pattern of low-dimensional distribution. Through manifold analysis of face pictures, we developed a novel age estimation framework. The manifold learning methods are applied to find a sufficient embedding space and model the low-dimensional manifold data with a multiple linear regression function. Experimental results on a large size age database demonstrate the effectiveness of the framework. To our best knowledge, this is the first work involving the manifold ways of age estimation.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
PublisherIEEE Computer Society
Pages1383-1386
Number of pages4
ISBN (Print)1424410177, 9781424410170
DOIs
StatePublished - Jan 1 2007
EventIEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, China
Duration: Jul 2 2007Jul 5 2007

Publication series

NameProceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

Other

OtherIEEE International Conference onMultimedia and Expo, ICME 2007
CountryChina
CityBeijing
Period7/2/077/5/07

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

Fingerprint Dive into the research topics of 'Estimating human age by manifold analysis of face pictures and regression on aging features'. Together they form a unique fingerprint.

Cite this