Feature extraction system for age estimation

Hironobu Fukai, Hironori Takimoto, Yasue Mitsukura, Minoru Fukumi

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

Abstract

In this paper, we propose the novel age estimation system with the real-coded genetic algorithm (RGA) and the neural network (NN). The age is one of important information in our living. There are a lot of studies on age estimation by the computer. However, the conventional method of the age estimation, the most of them are the studies intended for an actual age. Therefore, we pay attention to the mechanism of human age perception. The apparent age feature is extracted by the fourier transform, and the important spectrum for the age perception are selected by the RGA. The age is estimated by the 3 layered NN. It is considered that it can extract important age feature using the RGA and it can analyze the important feature area. In addition, proposed method extracts the age feature at each age. In order to show the effectiveness of the proposed method, we show the simulation examples. From the simulation results, we can confirm that the proposed method works well.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
Pages458-465
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2008 Dec 24
Externally publishedYes
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia
Duration: 2008 Sep 32008 Sep 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5178 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
CountryCroatia
CityZagreb
Period08/9/308/9/5

Keywords

  • Age estimation
  • Neural network (NN)
  • Real-coded genetic algorithm(RGA)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Fukai, H., Takimoto, H., Mitsukura, Y., & Fukumi, M. (2008). Feature extraction system for age estimation. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings (PART 2 ed., pp. 458-465). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5178 LNAI, No. PART 2). https://doi.org/10.1007/978-3-540-85565-1-57