Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
传统的特征提取方法主要有：主分量分析、奇异值分解、投影追踪、自组织映射等。
The algebraic feature extraction of images and the authors' research work on singular value vectors as a kind of algebraic features of images are emphasized.
重点介绍了图像的代数特征抽取以及作者关于奇异值特征矢量作为图像的一种代数特征方面的研究工作。
A feature extraction method of high-range-resolution radar profiles, which takes advantage of wavelet packet transform and modified SVD (singular value decomposition) was proposed.
提出了基于小波包变换和改进奇异值分解的高分辨雷达目标一维距离像特征提取方法。
Singular value is extracted as to feature of cylinder explosive noise signal from Cover Matrix with singular value theory.
利用奇异值理论提取包含矩阵的奇异值作为气缸爆发噪声信号的特征。
Here, we use the singular value decomposition and principal component analysis for facial feature extraction, using the average distance category as discrimination on the basis of authentication.
其中人脸特征提取采用了奇异值分解和主分量分析法，身份验证则采用了以类内平均距离为判据的算法。
Feature points' 3d coordinates are computed through singular value decomposition of projector matrix, then compute projector matrix by triangulation.
对应特征点的三维重建是根据三角测量的方法计算其投影矩阵，然后用奇异值分解求出特征点的三维齐次坐标。
Feature points' 3d coordinates are computed through singular value decomposition of projector matrix, then compute projector matrix by triangulation.
对应特征点的三维重建是根据三角测量的方法计算其投影矩阵，然后用奇异值分解求出特征点的三维齐次坐标。
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