Face Recognition Based on ICA Combined with FLD
Abstract
Recently in face recognition, as opposed to our expectation, the performance of an ICA (Independent Component Analysis) method combined with LDA (Linear Discriminant Analysis) was reported as lower than an ICA only based method. This research points out that (ICA+LDA) methods have not got a fair comparison for evaluating its recognition performance. In order to incorporate class specific information into ICA, we have employed FLD (Fisher Linear Discriminant) and have proposed our (ICA+FLD) method. In the experimental results, we report that our (ICA+FLD) method has better performance than ICA only based methods as well as other representative methods such as Eigenface and Fisherface methods.
Cite
Text
Yi et al. "Face Recognition Based on ICA Combined with FLD." European Conference on Computer Vision, 2002. doi:10.1007/3-540-47917-1_2Markdown
[Yi et al. "Face Recognition Based on ICA Combined with FLD." European Conference on Computer Vision, 2002.](https://mlanthology.org/eccv/2002/yi2002eccv-face/) doi:10.1007/3-540-47917-1_2BibTeX
@inproceedings{yi2002eccv-face,
title = {{Face Recognition Based on ICA Combined with FLD}},
author = {Yi, Juneho and Kim, Jongsun and Choi, Jongmoo and Han, JungHyun and Lee, Eunseok},
booktitle = {European Conference on Computer Vision},
year = {2002},
pages = {10-18},
doi = {10.1007/3-540-47917-1_2},
url = {https://mlanthology.org/eccv/2002/yi2002eccv-face/}
}