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SRC
- sparse representation algorithm
MatchingPursuits
- Matching Pursuit方法，经典的稀疏表示方法，可以用人脸识别和图像分类，图像去噪，现在非常流行。-Matching Pursuit method, sparse representation of the classic, you can use face recognition and image classification, image denoising, now very popular.
facial-features
- 运用于人脸识别中的特征提取方法：通过稀疏化特征向量（即使一些不重要的特征值为0），来减少运算量-Used in face recognition feature extraction methods: by sparse feature vector (even if some important features of value 0), to reduce the computation
2Dto3D
- 本文提出的基于稀疏线性模型的优化算法能够相对准确、稳定地估计出二维特征点的深度信息。将深度估计值应用于形变算法，可以提高人脸的重建精度。-The proposed model based on sparse linear optimization algorithm is relatively accurate and stable two-dimensional feature points to estimate the depth of information. Estimate the
l1benchmark
- 主要用于解决模式识别中稀疏表示人脸识别核心问题L1范数源代码，程序采用同伦算法设计的，在目前稀疏表示多种算法中，同伦算法是性能公认最好的.-Mainly used to solve the sparse representation of face recognition pattern recognition in the core of L1 norm source code, the program designed using the homotopy algorithm, sparse
face_recognitionsparserepresentation
- 人脸稀疏表示的经典文献，做人脸稀疏表示必看-Face the classic literature on sparse representation, sparse representation of human face must-see
PCA-Faces-and-examples
- 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.
P1_1-s2.0-S016786551400316X-main
- An Adaptive Bimodal Recognition Framework using Sparse Coding for Face and Ear
robust
- 2篇基于稀疏表示具有鲁棒性人脸识别算法介绍，pdf格式-2 piece based on sparse representation robust face recognition algorithm is introduced, in PDF format
Sparse-Lowrank-Approximation
- 基于稀疏表示和低秩逼近的人脸识别新方法，对于研究生物特征识别的朋友可以作为参考-The sparse and low rank approximation of the face recognition method based on the research on biological feature recognition, friends can be used as reference
sparse-representation-pdf
- This project describes the problem of facial expression recognition in the field of computer vision. Firstly, the psychological background of the problem is presented. Then, the idea of facial expression recognition system (FERS) is outlined and the