Modelling geiometric features for face based age classification

Lin Lin Shen, Zhen Ji

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

As one of the important research areas in face processing, face based age classification could be very useful for the index of large face database. Though a few works have been proposed in literature, many up to date face processing technologies have not been applied and more attention shall be drawn to this area. In this paper, we developed both efficient and robust facial feature location algorithms and proposed a geometric feature based age classification system. The proposed nose and mouth location algorithm was tested using images with variant illumination, expression and pose changes. Based on the robust eyes, nose and mouth location algorithm, simple modeling of the geometric features provides a reasonable classifier for baby and adult classification. The proposed system was tested using hundreds of images downloaded from internet. Though the classification task is much more challenging, significantly better performance than earlier work in literature has been achieved.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Pages2927-2931
Number of pages5
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, China
Duration: 12 Jul 200815 Jul 2008

Publication series

NameProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Volume5

Conference

Conference7th International Conference on Machine Learning and Cybernetics, ICMLC
Country/TerritoryChina
CityKunming
Period12/07/0815/07/08

Keywords

  • Age classification
  • Facial feature location
  • Geometric feature

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Modelling geiometric features for face based age classification'. Together they form a unique fingerprint.

Cite this