This paper identifies a novel feature space to address the problem of human face recognition from still images. This based on the PCA space of the features extracted by a new multiresolution analysis tool called Fast Discrete Curvelet Transfo

Support vector regression has been proposed in a number of image processing tasks including blind image deconvolution, image denoising and single frame super-resolution. As for other machine learning methods, the training is slow. In this paper,

稀疏主成分分析用于脸部检测和识别的基础知识介绍。初学者很专业的入门材料。-Sparse principal component analysis for face detection and identification of the basics of introduction. Introductory material for beginners very professional.

The key concept in principal component analysis (PCA) is to reduce a high dimensional data volume into a lower dimensional space, where the low dimensional data con-tams most of the useful information/variance contained in the original data set. The