Publication result detail

Neural network for classifying faces by gender

HABR, M., ŠTEFÍČEK, R.

Original Title

Neural network for classifying faces by gender

English Title

Neural network for classifying faces by gender

Type

Paper in proceedings (conference paper)

Original Abstract

In this paper we present an overview of the using of the Principal components analysis for face recognition using neural networks. Using gender as discriminative features improve the classification robustness. As we show the faces are different only by one eigenvector. By changing one of the eigenvectors we can generate a different person-image. This property will be used for classification face images by gender.

English abstract

In this paper we present an overview of the using of the Principal components analysis for face recognition using neural networks. Using gender as discriminative features improve the classification robustness. As we show the faces are different only by one eigenvector. By changing one of the eigenvectors we can generate a different person-image. This property will be used for classification face images by gender.

Key words in English

neural networks, principal components analysis, eigenvector, face classification

Authors

HABR, M., ŠTEFÍČEK, R.

Released

05.09.2002

Location

Brno

ISBN

80-214-2172-X

Book

Telecommunications and Signal Processing

Pages from

134

Pages count

4

BibTex

@inproceedings{BUT5309,
  author="Martin {Habr} and Richard {Štefíček}",
  title="Neural network for classifying faces by gender",
  booktitle="Telecommunications and Signal Processing",
  year="2002",
  pages="4",
  address="Brno",
  isbn="80-214-2172-X"
}