Robust gender and age estimation under varying facial pose

Hironori Takimoto, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

研究成果: Article

16 引用 (Scopus)

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This paper presents a method for gender and age estimation which is robust to changing facial pose. We propose a feature point detection method, called the adapted retinal sampling method (ARSM), and a feature extraction method. A basic concept of the ARSM is to add knowledge about the facial structure to the retinal sampling method. In this method, feature points are detected on the basis of seven points corresponding to facial organs from a facial image. The reason why we used seven points as the basis of feature point detection is that facial organs are conspicuous in the facial region, and are comparatively easy to extract. As features robust to changing facial pose, skin texture, hue, and the Gabor jet are used for gender and age estimation. For classification of gender and estimation of age, we use a multilayered neural network. We also examine the left-right symmetry of faces in connection with gender and age estimation by the proposed method.

元の言語English
ページ(範囲)32-40
ページ数9
ジャーナルElectronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi)
91
発行部数7
DOI
出版物ステータスPublished - 2008
外部発表Yes

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Physics and Astronomy(all)
  • Signal Processing
  • Applied Mathematics

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