Independent component representations for face recognition

  title={Independent component representations for face recognition},
  author={Marian Stewart Bartlett and Martin Lades and Terrence J. Sejnowski},
  booktitle={Human Vision and Electronic Imaging},
In a task such as face recognition, much of the important information may be contained in the high-order relationships among the image pixels. A number of face recognition algorithms employ principal component analysis (PCA), which is based on the second-order statistics of the image set, and does not address high-order statistical dependencies such as the relationships among three or more pixels. Independent component analysis (ICA) is a generalization of PCA which separates the high-order… CONTINUE READING
Highly Influential
This paper has highly influenced 31 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 538 citations. REVIEW CITATIONS
241 Extracted Citations
13 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.

539 Citations

Citations per Year
Semantic Scholar estimates that this publication has 539 citations based on the available data.

See our FAQ for additional information.

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 13 references

Velantin, \Low-dimensional representation of faces in higher dimen sions of the face space.,

  • H. OToole, Abdi, K. De enbacher
  • Journal of the Optical Society of America A
  • 1993

Face, gender and emotion recognition using holons," in Advances in Neural Information

  • G. Cottrell, J. . Metcalfe
  • Processing Systems, D. Touretzky, ed.,
  • 1991

Similar Papers

Loading similar papers…