A Compared Study Between Some Subspace Based Algorithms
Computer Vision and Pattern Recognition
2019-12-24 v1 Machine Learning
Abstract
The technology of face recognition has made some progress in recent years. After studying the PCA, 2DPCA, R1-PCA, L1-PCA, KPCA and KECA algorithms, in this paper ECA (2DECA) is proposed by extracting features in PCA (2DPCA) based on Renyi entropy contribution. And then we conduct a study on the 2DL1-PCA and 2DR1-PCA algorithms. On the basis of the experiments, this paper compares the difference of the recognition accuracy and operational efficiency between the above algorithms.
Keywords
Cite
@article{arxiv.1912.10657,
title = {A Compared Study Between Some Subspace Based Algorithms},
author = {Xing Liu and Xiao-Jun Wu and Zhen Liu and He-Feng Yin},
journal= {arXiv preprint arXiv:1912.10657},
year = {2019}
}
Comments
13 pages, 5 figures