节点文献
基于图谱分解的人脸表情分析
Facial Expression Analysis Based on Graph Spectral Decomposition
【摘要】 文中探索用人脸的几何结构图谱方法嵌入到模式空间来分析人脸表情,以图的加权邻接矩阵主要特征向量来定义矩阵的特征模。计算谱特征向量-模间邻接矩阵。用两类模式向量在范数下的多维尺度变换方法(MDS)嵌入该向量到一个模式空间,用人脸特征点来表示人脸图,并在模式空间里描述该嵌入方法下的同一人脸的不同表情。
【Abstract】 In this paper explore how to use spectral methods of geometry structural graph for analyzing facial expression and clustering in the pattern-space.Use the leading eigenvectors of the weighted graph adjacency matrix to define eigenmodes of the adjacency matrix.For each eigenmode,compute vectors of spectral properties.It includes the leading inter-mode adjacency matrices.Embed these vectors in a pattern-space using multidimensional scaling on the norm for pairs of patten vectors.Illustrate the utility of the embedding methods representing the arrangement of facial expression of dissimilar human face in the pattern-space.
【Key words】 graph spectra; human face recognition; analysis of facial expression; multidimensional scaling;
- 【文献出处】 计算机技术与发展 ,Computer Technology and Development , 编辑部邮箱 ,2006年04期
- 【分类号】TP391.41
- 【被引频次】3
- 【下载频次】226