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Pacific-Rim Symposium on Image and Video Technology

PSIVT 2011: Advances in Image and Video Technology pp 116–127Cite as

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Gender Identification Using Feature Patch-Based Bayesian Classifier

Gender Identification Using Feature Patch-Based Bayesian Classifier

  • Shen-Ju Lin17,
  • Chung-Lin Huang17 &
  • Shih-Chung Hsu17 
  • Conference paper
  • 1454 Accesses

  • 1 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7088)

Abstract

In the paper, we propose a Bayesian classifier which exploits non-parametric model to identify the gender from the facial images. Our major contribution is that we use feature patch-based non-parametric method to generate the posteriori of male and female based on the characteristics of the labeled training image patches. Our system consists of four modules. First, we use AAM model to identify facial feature points. Facial images are represented by the overlapping feature patches around the feature points. Second, from the labeled training patches, we select a smaller subset as the patch library based on the K means clustering. Third, in training, we embed the gender characteristics of the training feature patches as the posteriori of the library patches. Fourth, in testing, we integrate the posterior of the test patches to determine the gender. The experimental results demonstrate that our proposed method is better than the conventional non-feature-patch-based methods.

Keywords

  • Gender identification
  • Active Appearance Model
  • Patches-based Bayesian estimation

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References

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan, R.O.C.

    Shen-Ju Lin, Chung-Lin Huang & Shih-Chung Hsu

Authors
  1. Shen-Ju Lin
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  2. Chung-Lin Huang
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  3. Shih-Chung Hsu
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Editor information

Editors and Affiliations

  1. Gwangju Institute of Science and Technology (GIST), 1 Oryong-dong Buk-gu, 500-712, Gwangju, South Korea

    Yo-Sung Ho

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© 2011 Springer-Verlag Berlin Heidelberg

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Lin, SJ., Huang, CL., Hsu, SC. (2011). Gender Identification Using Feature Patch-Based Bayesian Classifier. In: Ho, YS. (eds) Advances in Image and Video Technology. PSIVT 2011. Lecture Notes in Computer Science, vol 7088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25346-1_11

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  • DOI: https://doi.org/10.1007/978-3-642-25346-1_11

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