Detail publikace

Face Representation and Tracking Using Gabor Wavelet Networks

Originální název

Face Representation and Tracking Using Gabor Wavelet Networks

Anglický název

Face Representation and Tracking Using Gabor Wavelet Networks

Jazyk

en

Originální abstrakt

This work presents a one of the approaches to human gesture recognition. A method where a discrete face template is represented by linear combination of the 2D odd-Gabor wavelet functions (Gabor Wavelet Network) is proposed. Using wavelet networks, an effective face representation and tracking method is achieved that is robust to changes and deformations of the face image. Possibilities of cooperation between a GWN and others methods for robust facial expressions recognition are also discussed, for example: Principal Component Analysis (PCA) and parameterized models of optical flow.

Anglický abstrakt

This work presents a one of the approaches to human gesture recognition. A method where a discrete face template is represented by linear combination of the 2D odd-Gabor wavelet functions (Gabor Wavelet Network) is proposed. Using wavelet networks, an effective face representation and tracking method is achieved that is robust to changes and deformations of the face image. Possibilities of cooperation between a GWN and others methods for robust facial expressions recognition are also discussed, for example: Principal Component Analysis (PCA) and parameterized models of optical flow.

BibTex 


@inproceedings{BUT10927,
  author="Michal {Španěl} and Pavel {Zemčík}",
  title="Face Representation and Tracking Using Gabor Wavelet Networks",
  annote="This work presents a one of the approaches to human gesture
recognition. A method where a discrete face template is represented by
linear combination of the 2D odd-Gabor wavelet functions (Gabor Wavelet
Network) is proposed. Using wavelet networks, an effective face
representation and tracking method is achieved that is robust to
changes and deformations of the face image. Possibilities of
cooperation between a GWN and others methods for robust facial
expressions recognition are also discussed, for example: Principal
Component Analysis (PCA) and parameterized models of optical flow.
",
  booktitle="Proceedings of the Central European Seminar on Computer Graphics",
  chapter="10927",
  year="2003",
  month="april",
  pages="163--169",
  type="conference paper"
}