@inproceedings{3fba4d9215ad46cfa64955c86c4e5406,
title = "Bi-dierectional PCA with assembled matrix distance metric",
abstract = "Principal Component Analysis (PCA) has been very successful in image recognition. Recent researches on PCAbased methods are mainly concentrated on two issues, feature extraction and classification. In this paper we propose BiDirectional PCA (BDPCA) with assembled matrix distance (AMD) metric to simultaneously deal with these two issues. For feature extraction, we propose a BDPCA approach which can reduce the dimension of the original image matrix in both column and row directions. For classification, we present an AMD metric to calculate the distance between two feature matrices. The results of our experiments show that, BDPCA with AMD metric is very effective in image recognition.",
keywords = "2DPCA, Face recognition, Image recognition, PCA, Palmprint recognition",
author = "Wangmeng Zuo and Kuanquan Wang and David Zhang",
year = "2005",
doi = "10.1109/ICIP.2005.1530216",
language = "英语",
isbn = "0780391349",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "958--961",
booktitle = "IEEE International Conference on Image Processing 2005, ICIP 2005",
note = "IEEE International Conference on Image Processing 2005, ICIP 2005 ; Conference date: 11-09-2005 Through 14-09-2005",
}