Institute Homepage DE Sign In

Back

Empirical Inference Conference Paper 2002

Gender Classification of Human Faces

Thumb ticker sm thumb felix a. wichmann
Empirical Inference
Felix A. Wichmann
  • Research Scientist

This paper addresses the issue of combining pre-processing methods—dimensionality reduction using Principal Component Analysis (PCA) and Locally Linear Embedding (LLE)—with Support Vector Machine (SVM) classification for a behaviorally important task in humans: gender classification. A processed version of the MPI head database is used as stimulus set. First, summary statistics of the head database are studied. Subsequently the optimal parameters for LLE and the SVM are sought heuristically. These values are then used to compare the original face database with its processed counterpart and to assess the behavior of a SVM with respect to changes in illumination and perspective of the face images. Overall, PCA was superior in classification performance and allowed linear separability.

Author(s): Graf, ABA. and Wichmann, FA.
Book Title: Biologically Motivated Computer Vision
Journal: Biologically Motivated Computer Vision 2002
Pages: 1-18
Year: 2002
Month: November
Day: 0
Editors: B{\"u}lthoff, H. H., S.W. Lee, T. A. Poggio and C. Wallraven
Publisher: Springer
Bibtex Type: Conference Paper (inproceedings)
Address: Berlin, Germany
DOI: 10.1007/3-540-36181-2_49
Event Name: Second International Workshop on Biologically Motivated Computer Vision (BMCV 2002)
Event Place: Tübingen, Germany
Digital: 0
Electronic Archiving: grant_archive
ISBN: 3-540-36181-2
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex 

@inproceedings{1815,
  title = {Gender Classification of Human Faces},
  journal = {Biologically Motivated Computer Vision 2002},
  booktitle = {Biologically Motivated Computer Vision},
  abstract = {This paper addresses the issue of combining pre-processing methods—dimensionality reduction using Principal Component Analysis (PCA) and Locally Linear Embedding (LLE)—with Support Vector Machine (SVM) classification for a behaviorally important task in humans: gender classification. A processed version of the MPI head database is used as stimulus set. First, summary statistics of the head database are studied. Subsequently the optimal parameters for LLE and the SVM are sought heuristically. These values are then used to compare the original face database with its processed counterpart and to assess the behavior of a SVM with respect to changes in illumination and perspective of the face images. Overall, PCA was superior in classification performance and allowed linear separability. },
  pages = {1-18},
  editors = {B{\"u}lthoff, H. H., S.W. Lee, T. A. Poggio and C. Wallraven},
  publisher = {Springer},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Berlin, Germany},
  month = nov,
  year = {2002},
  slug = {1815},
  author = {Graf, ABA. and Wichmann, FA.},
  month_numeric = {11}
}