Is ICA significantly better than PCA for face recognition?

Jian Yang, Dapeng Zhang, Jing Yu Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

29 Citations (Scopus)

Abstract

The standard PCA was always used as baseline algorithm to evaluate ICA-based face recognition systems in the previous research. In this paper, we examine the two architectures of ICA for image representation and find that ICA Architecture I involves a PCA process by vertically centering (PCA I), while ICA Architecture II involves a whitened PCA process by horizontally centering (PCA II). So, it is reasonable to use these two PCA versions as baseline algorithms to revaluate the ICA-based face recognition systems. The experiments were performed on the FERET face database. The experimental results show there is no significant performance differences between ICA Architecture I (II) and PCA I (II), although ICA Architecture II significantly outperforms the standard PCA. It can be concluded that the performance of ICA strongly depends on its involved PCA process. The pure ICA projection has little effect on the performance of face recognition.
Original languageEnglish
Title of host publicationProceedings - 10th IEEE International Conference on Computer Vision, ICCV 2005
Pages198-203
Number of pages6
VolumeI
DOIs
Publication statusPublished - 1 Dec 2005
EventProceedings - 10th IEEE International Conference on Computer Vision, ICCV 2005 - Beijing, China
Duration: 17 Oct 200520 Oct 2005

Conference

ConferenceProceedings - 10th IEEE International Conference on Computer Vision, ICCV 2005
Country/TerritoryChina
CityBeijing
Period17/10/0520/10/05

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this