.png){kind=icon}
返回
Graph Regularized Sparsity Discriminant Analysis for face recognition
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2015.04.116.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Manifold learning and Sparse Representation Classifier are two popular techniques for face recognition. Because manifold learning can find low-dimensional representations for high-dimensional data, it is widely applied in computer vision and pattern recognition. Most of the manifold learning algorithms can be unified in the graph embedding framework, where the first step is to determine the adjacent graphs. Traditional methods use k nearest neighbor or the e-ball schemes. However, they are parametric and sensitive to noises. Moreover, it is hard to determine the size of appropriate neighborhoods. To deal with these problems, in this paper, Graph Regularized Sparsity Discriminant Analysis, GRSDA, for short, is proposed. Based on graph embedding and sparsity preserving projection, the weight matrices for intrinsic and penalty graphs are obtained through sparse representation. GRSDA seeks a subspace in which samples in intra-classes are as compact as possible while samples in inter-classes are as separable as possible. Specifically, samples in the low-dimensional space can preserve the sparse locality relationship in the same class, while enhancing the separability for samples in different classes. Hence, GRSDA can achieve better performance. Extensive experiments were carried out on ORI YALE-B and AR face databases, and the results confirmed that the proposed algorithm outperformed LPP, UDP, SPP and DSNPE. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Sparse representation
Graph embedding
Sparsity preserving projection
Feature extraction
Face recognition
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
.png){kind=icon}
Principal manifolds and nonlinear dimensionality reduction via tangent space alignment基于切线空间对齐的主流形和非线性降维
OAAI
OAAI分享收藏分享收藏Insights into the Corrosion of Pd-Pt-Co Core-Shell Nanocubes and Their Evolved Heterostructures as Active Methanol Oxidation Reaction Electrocatalysts对pd-pt-co核壳纳米立方体的腐蚀及其演变的异质结构作为活性甲醇氧化反应电催化剂的见解
PREAI
分享收藏
查看更多内容