Description: Sparse Representation or Collaborative Representation: Which Helps Face Recognition? This code devotes to analyze the working mechanism of SRC, and indicates that it is the CR but not the l1-norm sparsity that makes SRC powerful for face classification. Platform: |
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Author:674946694@qq.com |
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Description: 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. Platform: |
Size: 1880064 |
Author:高尚兵 |
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Description: 该源码实现了使用基于稀疏表示的人脸识别算法。使用GPSR作为l1模最小化方法。-This pack of code implement a imges-based face recognition using sparse representation classification. In the algorithm, i employ GPSR as tool to complete the optimization procedure of l1-minimization. Platform: |
Size: 8192 |
Author:zhang chao |
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Description: 基于稀疏表示的人脸识别，里面有9种求1范数的方法-Face recognition based on sparse representation, there are nine kinds of seeking a method of norm Platform: |
Size: 78848 |
Author:wangqiang |
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Description: 强壮的人脸识别系统，发表于cvpr2011年，程序是应用matlab实现-Recently the sparse representation (or coding) based classifi cation (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as
a sparse linear combination of the training samples, and
the representation fi delity is measured by the � 2-norm or
� 1-norm of coding residual. Such a sparse coding model
actually assumes that the coding residual follows Gaus-
sian or Laplacian distribution, which may not be accurate
enough to describe the coding errors in practice. In this
paper, we propose a new scheme, namely the robust sparse
coding (RSC), by modeling the sparse coding as a sparsity-
constrained robust regression problem. The RSC seeks for
the MLE (maximum likelihood estimation) solution of the
sparse coding problem, and it is much more robust to out-
liers (e.g., occlusions, corruptions, etc.) than SRC. An
effi cient iteratively reweighted sparse coding algorithm is
proposed to solve the RSC model. Extensive Platform: |
Size: 1216512 |
Author:刘大明 |
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Description: 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 representation in a variety of current algorithms, the homotopy algorithm is recognized as the best performance. Platform: |
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Author: |
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Description: 发表于ECCV上的一篇用于人脸识别的算法，Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary -At ECCV on an algorithm for face recognition, Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary Platform: |
Size: 13312 |
Author:joe |
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Description: 用matlab实现的基于稀疏表示的人脸识别方法。其中解稀疏表示时，包含了各种方法。-Using matlab face recognition method based on sparse representation. Solution of the sparse representation, contains a variety of methods. Platform: |
Size: 47104 |
Author:wangbinbin |
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Description: 稀疏表示在鲁棒性人脸识别中的应用，很经典的论文-Sparse representation in the robustness of face recognition, very classic papers Platform: |
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Author:宋明龙 |
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Description: In this paper, we propose a two-phase test sample
representation method for face recognition. The first phase of
the proposed method seeks to represent the test sample as
a linear combination of all the training samples and exploits
the representation ability of each training sample to determine
M “nearest neighbors” for the test sample. The second phase
represents the test sample as a linear combination of the
determined M nearest neighbors and uses the representation
result to perform classification. We propose this method with the
following assumption: the test sample and its some neighbors
are probably from the same class. Thus, we use the first phase
to detect the training samples that are far from the test sample
and assume that these samples have no effects on the ultimate
classification decision. This is helpful to accurately classify the
test sample. We will also show the probability explanation of
the proposed method. A number of face recognition experiments
show that our method performs very well. Platform: |
Size: 460458 |
Author:may@uestc.edu.cn |
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Description: 稀疏表示用于人脸识别，采用SDR方法，文字发表在IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE顶级期刊，影响因子4.75.-Sparse representation for face recognition, the use of the SDR method, text published in the IEEE Transactions on pattern analysis and machine intelligence top journals, impact factor of 4.75. Platform: |
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Author:moyan |
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Description: 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 requirements are specified. The FER system consists of 3 stages: face detection, feature extraction and expression recognition. Methods proposed in literature are reviewed for each stage of a system. Finally, the design and implementation of this system are explained. The face detection algorithm used in the system is based on Viola-Jones. The features are obtained using Gabor features. The MultiSupport Vector Machine is used for classification. The used for facial expression system is JAFFE Database-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 requirements are specified. The FER system consists of 3 stages: face detection, feature extraction and expression recognition. Methods proposed in literature are reviewed for each stage of a system. Finally, the design and implementation of this system are explained. The face detection algorithm used in the system is based on Viola-Jones. The features are obtained using Gabor features. The MultiSupport Vector Machine is used for classification. The used for facial expression system is JAFFE Database Platform: |
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Author:Jashpreet |
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Description: 稀疏表示经典著作
John Wright et al, Robust Face Recognition via Sparse Representation , PAMI 2009的程序-# impFaceRecognition
A Matlab implementation of Face Recognition using Sparse Representation the original paper:
John Wright et al, Robust Face Recognition via Sparse Representation , PAMI 2009.
In our implementation, we propose a Multi-scale Sparse Representation to improve the performance compared to the original paper.
If you use our code, please cite the paper:
Multi-scale Sparse Representation for Robust Face Recognition
Platform: |
Size: 773120 |
Author:杨森泉 |
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Description: 稀疏表示的毕业参考论文，在图像去噪、图像修复、人脸识别及压缩感知等图像处理领域中的应用进行了总结.-Sparse representation of graduation reference papers, summarized in the image denoising, image restoration, face recognition and compressed sensing and other image processing applications Platform: |
Size: 2722816 |
Author:zhu |
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Search - Sparse Representation Face